id sid tid token lemma pos cana-844 1 1 communications communication NOUN cana-844 1 2 on on ADP cana-844 1 3 applied apply VERB cana-844 1 4 nonlinear nonlinear ADJ cana-844 1 5 analysis analysis NOUN cana-844 1 6 issn issn NOUN cana-844 1 7 : : PUNCT cana-844 1 8 1074 1074 NUM cana-844 1 9 - - PUNCT cana-844 1 10 133x 133x NUM cana-844 1 11 vol vol NOUN cana-844 1 12 31 31 NUM cana-844 1 13 no no NOUN cana-844 1 14 . . PUNCT cana-844 2 1 4s 4s NUM cana-844 2 2 ( ( PUNCT cana-844 2 3 2024 2024 NUM cana-844 2 4 ) ) PUNCT cana-844 2 5 229 229 NUM cana-844 3 1 https://internationalpubls.com https://internationalpubls.com X cana-844 3 2 computational computational ADJ cana-844 3 3 predictions prediction NOUN cana-844 3 4 of of ADP cana-844 3 5 mgmt mgmt PROPN cana-844 3 6 promoter promoter NOUN cana-844 3 7 methylation methylation NOUN cana-844 3 8 in in ADP cana-844 3 9 gliomas glioma NOUN cana-844 3 10 : : PUNCT cana-844 3 11 a a DET cana-844 3 12 mathematical mathematical ADJ cana-844 3 13 radiogenomics radiogenomic NOUN cana-844 3 14 approach approach NOUN cana-844 3 15 ayesha ayesha PROPN cana-844 3 16 agrawal1 agrawal1 PROPN cana-844 3 17 , , PUNCT cana-844 3 18 v. v. ADP cana-844 3 19 maan2 maan2 PROPN cana-844 3 20 1department 1department NUM cana-844 3 21 of of ADP cana-844 3 22 computer computer NOUN cana-844 3 23 science science PROPN cana-844 3 24 & & CCONJ cana-844 3 25 engineering engineering PROPN cana-844 3 26 , , PUNCT cana-844 3 27 mody mody PROPN cana-844 3 28 university university NOUN cana-844 3 29 , , PUNCT cana-844 3 30 india india PROPN cana-844 3 31 2department 2department NUM cana-844 3 32 of of ADP cana-844 3 33 computer computer NOUN cana-844 3 34 science science PROPN cana-844 3 35 & & CCONJ cana-844 3 36 engineering engineering PROPN cana-844 3 37 , , PUNCT cana-844 3 38 mody mody PROPN cana-844 3 39 university university PROPN cana-844 3 40 , , PUNCT cana-844 3 41 india india PROPN cana-844 3 42 emails email NOUN cana-844 3 43 : : PUNCT cana-844 3 44 aishaagrawal33@gmail.com1 aishaagrawal33@gmail.com1 ADJ cana-844 3 45 , , PUNCT cana-844 3 46 vinodmaan.cet@modyuniversity.ac.in2 vinodmaan.cet@modyuniversity.ac.in2 VERB cana-844 3 47 article article NOUN cana-844 3 48 history history NOUN cana-844 3 49 : : PUNCT cana-844 3 50 received receive VERB cana-844 3 51 : : PUNCT cana-844 3 52 20 20 NUM cana-844 3 53 - - PUNCT cana-844 3 54 04 04 NUM cana-844 3 55 - - PUNCT cana-844 3 56 2024 2024 NUM cana-844 3 57 revised revise VERB cana-844 3 58 : : PUNCT cana-844 3 59 12 12 NUM cana-844 3 60 - - PUNCT cana-844 3 61 06 06 NUM cana-844 3 62 - - PUNCT cana-844 3 63 2024 2024 NUM cana-844 3 64 accepted accept VERB cana-844 3 65 : : PUNCT cana-844 3 66 24 24 NUM cana-844 3 67 - - PUNCT cana-844 3 68 06 06 NUM cana-844 3 69 - - PUNCT cana-844 3 70 2024 2024 NUM cana-844 3 71 abstract abstract NOUN cana-844 3 72 : : PUNCT cana-844 3 73 in in ADP cana-844 3 74 the the DET cana-844 3 75 treatment treatment NOUN cana-844 3 76 of of ADP cana-844 3 77 glioblastomas glioblastoma NOUN cana-844 3 78 , , PUNCT cana-844 3 79 non non ADJ cana-844 3 80 - - ADJ cana-844 3 81 invasive invasive ADJ cana-844 3 82 methods method NOUN cana-844 3 83 for for ADP cana-844 3 84 determining determine VERB cana-844 3 85 mgmt mgmt ADJ cana-844 3 86 gene gene NOUN cana-844 3 87 promoter promoter NOUN cana-844 3 88 methylation methylation NOUN cana-844 3 89 status status NOUN cana-844 3 90 are be AUX cana-844 3 91 crucial crucial ADJ cana-844 3 92 due due ADP cana-844 3 93 to to ADP cana-844 3 94 their their PRON cana-844 3 95 implications implication NOUN cana-844 3 96 for for ADP cana-844 3 97 chemotherapy chemotherapy NOUN cana-844 3 98 responsiveness responsiveness NOUN cana-844 3 99 . . PUNCT cana-844 4 1 this this DET cana-844 4 2 study study NOUN cana-844 4 3 utilizes utilize VERB cana-844 4 4 a a DET cana-844 4 5 mathematical mathematical ADJ cana-844 4 6 and and CCONJ cana-844 4 7 computational computational ADJ cana-844 4 8 framework framework NOUN cana-844 4 9 to to PART cana-844 4 10 extract extract VERB cana-844 4 11 and and CCONJ cana-844 4 12 analyze analyze VERB cana-844 4 13 radiogenomic radiogenomic ADJ cana-844 4 14 data datum NOUN cana-844 4 15 from from ADP cana-844 4 16 mri mri NOUN cana-844 4 17 images image NOUN cana-844 4 18 to to PART cana-844 4 19 predict predict VERB cana-844 4 20 the the DET cana-844 4 21 methylation methylation NOUN cana-844 4 22 status status NOUN cana-844 4 23 . . PUNCT cana-844 5 1 the the DET cana-844 5 2 first first ADJ cana-844 5 3 step step NOUN cana-844 5 4 in in ADP cana-844 5 5 our our PRON cana-844 5 6 framework framework NOUN cana-844 5 7 involves involve VERB cana-844 5 8 extracting extract VERB cana-844 5 9 radiogenomic radiogenomic ADJ cana-844 5 10 data datum NOUN cana-844 5 11 from from ADP cana-844 5 12 mri mri NOUN cana-844 5 13 images image NOUN cana-844 5 14 . . PUNCT cana-844 6 1 this this DET cana-844 6 2 process process NOUN cana-844 6 3 requires require VERB cana-844 6 4 sophisticated sophisticated ADJ cana-844 6 5 image image NOUN cana-844 6 6 processing processing NOUN cana-844 6 7 techniques technique NOUN cana-844 6 8 to to PART cana-844 6 9 convert convert VERB cana-844 6 10 mri mri NOUN cana-844 6 11 scans scan NOUN cana-844 6 12 into into ADP cana-844 6 13 a a DET cana-844 6 14 format format NOUN cana-844 6 15 suitable suitable ADJ cana-844 6 16 for for ADP cana-844 6 17 machine machine NOUN cana-844 6 18 learning learn VERB cana-844 6 19 analysis analysis NOUN cana-844 6 20 . . PUNCT cana-844 7 1 the the DET cana-844 7 2 features feature NOUN cana-844 7 3 extracted extract VERB cana-844 7 4 include include VERB cana-844 7 5 textural textural ADJ cana-844 7 6 patterns pattern NOUN cana-844 7 7 , , PUNCT cana-844 7 8 intensity intensity NOUN cana-844 7 9 distributions distribution NOUN cana-844 7 10 , , PUNCT cana-844 7 11 and and CCONJ cana-844 7 12 other other ADJ cana-844 7 13 relevant relevant ADJ cana-844 7 14 radiomic radiomic PROPN cana-844 7 15 characteristics.to characteristics.to X cana-844 7 16 identify identify VERB cana-844 7 17 the the DET cana-844 7 18 most most ADV cana-844 7 19 significant significant ADJ cana-844 7 20 features feature NOUN cana-844 7 21 , , PUNCT cana-844 7 22 we we PRON cana-844 7 23 employ employ VERB cana-844 7 24 a a DET cana-844 7 25 random random ADJ cana-844 7 26 forest forest NOUN cana-844 7 27 ( ( PUNCT cana-844 7 28 rf rf NOUN cana-844 7 29 ) ) PUNCT cana-844 7 30 algorithm algorithm NOUN cana-844 7 31 . . PUNCT cana-844 8 1 mathematically mathematically ADV cana-844 8 2 , , PUNCT cana-844 8 3 rf rf PRON cana-844 8 4 is be AUX cana-844 8 5 an an DET cana-844 8 6 ensemble ensemble ADJ cana-844 8 7 learning learning NOUN cana-844 8 8 method method NOUN cana-844 8 9 that that PRON cana-844 8 10 operates operate VERB cana-844 8 11 by by ADP cana-844 8 12 constructing construct VERB cana-844 8 13 multiple multiple ADJ cana-844 8 14 decision decision NOUN cana-844 8 15 trees tree NOUN cana-844 8 16 during during ADP cana-844 8 17 training training NOUN cana-844 8 18 and and CCONJ cana-844 8 19 outputting output VERB cana-844 8 20 the the DET cana-844 8 21 mode mode NOUN cana-844 8 22 of of ADP cana-844 8 23 the the DET cana-844 8 24 classes class NOUN cana-844 8 25 for for ADP cana-844 8 26 classification classification NOUN cana-844 8 27 tasks task NOUN cana-844 8 28 . . PUNCT cana-844 9 1 the the DET cana-844 9 2 importance importance NOUN cana-844 9 3 of of ADP cana-844 9 4 each each DET cana-844 9 5 feature feature NOUN cana-844 9 6 is be AUX cana-844 9 7 evaluated evaluate VERB cana-844 9 8 based base VERB cana-844 9 9 on on ADP cana-844 9 10 its its PRON cana-844 9 11 contribution contribution NOUN cana-844 9 12 to to ADP cana-844 9 13 the the DET cana-844 9 14 accuracy accuracy NOUN cana-844 9 15 of of ADP cana-844 9 16 the the DET cana-844 9 17 model model NOUN cana-844 9 18 , , PUNCT cana-844 9 19 quantified quantify VERB cana-844 9 20 by by ADP cana-844 9 21 metrics metric NOUN cana-844 9 22 such such ADJ cana-844 9 23 as as ADP cana-844 9 24 gini gini NOUN cana-844 9 25 impurity impurity NOUN cana-844 9 26 or or CCONJ cana-844 9 27 information information NOUN cana-844 9 28 gain gain NOUN cana-844 9 29 . . PUNCT cana-844 10 1 employing employ VERB cana-844 10 2 advanced advanced ADJ cana-844 10 3 machine machine NOUN cana-844 10 4 learning learning NOUN cana-844 10 5 models model NOUN cana-844 10 6 like like ADP cana-844 10 7 vgg19 vgg19 PROPN cana-844 10 8 , , PUNCT cana-844 10 9 resnet50 resnet50 NOUN cana-844 10 10 , , PUNCT cana-844 10 11 and and CCONJ cana-844 10 12 sequential sequential ADJ cana-844 10 13 fcnet fcnet ADJ cana-844 10 14 artificial artificial ADJ cana-844 10 15 neural neural ADJ cana-844 10 16 networks network NOUN cana-844 10 17 , , PUNCT cana-844 10 18 alongside alongside ADP cana-844 10 19 traditional traditional ADJ cana-844 10 20 classifiers classifier NOUN cana-844 10 21 such such ADJ cana-844 10 22 as as ADP cana-844 10 23 naive naive ADJ cana-844 10 24 bayes bayes NOUN cana-844 10 25 and and CCONJ cana-844 10 26 logistic logistic ADJ cana-844 10 27 regression regression NOUN cana-844 10 28 , , PUNCT cana-844 10 29 we we PRON cana-844 10 30 analyze analyze VERB cana-844 10 31 features feature NOUN cana-844 10 32 identified identify VERB cana-844 10 33 by by ADP cana-844 10 34 a a DET cana-844 10 35 random random ADJ cana-844 10 36 forest forest NOUN cana-844 10 37 algorithm algorithm NOUN cana-844 10 38 . . PUNCT cana-844 11 1 our our PRON cana-844 11 2 mathematical mathematical ADJ cana-844 11 3 approach approach NOUN cana-844 11 4 ensures ensure VERB cana-844 11 5 rigorous rigorous ADJ cana-844 11 6 evaluation evaluation NOUN cana-844 11 7 of of ADP cana-844 11 8 model model NOUN cana-844 11 9 accuracy accuracy NOUN cana-844 11 10 through through ADP cana-844 11 11 sensitivity sensitivity NOUN cana-844 11 12 , , PUNCT cana-844 11 13 specificity specificity NOUN cana-844 11 14 , , PUNCT cana-844 11 15 and and CCONJ cana-844 11 16 other other ADJ cana-844 11 17 performance performance NOUN cana-844 11 18 metrics metric NOUN cana-844 11 19 , , PUNCT cana-844 11 20 presenting present VERB cana-844 11 21 the the DET cana-844 11 22 sequential sequential ADJ cana-844 11 23 fcnet fcnet NOUN cana-844 11 24 ann ann PROPN cana-844 11 25 combined combine VERB cana-844 11 26 with with ADP cana-844 11 27 resnet50 resnet50 NOUN cana-844 11 28 as as ADP cana-844 11 29 the the DET cana-844 11 30 superior superior ADJ cana-844 11 31 model model NOUN cana-844 11 32 . . PUNCT cana-844 12 1 this this DET cana-844 12 2 research research NOUN cana-844 12 3 contributes contribute VERB cana-844 12 4 to to ADP cana-844 12 5 the the DET cana-844 12 6 field field NOUN cana-844 12 7 of of ADP cana-844 12 8 precision precision NOUN cana-844 12 9 healthcare healthcare NOUN cana-844 12 10 by by ADP cana-844 12 11 enhancing enhance VERB cana-844 12 12 the the DET cana-844 12 13 mathematical mathematical ADJ cana-844 12 14 methods method NOUN cana-844 12 15 used use VERB cana-844 12 16 in in ADP cana-844 12 17 the the DET cana-844 12 18 non non ADJ cana-844 12 19 - - ADJ cana-844 12 20 invasive invasive ADJ cana-844 12 21 diagnosis diagnosis NOUN cana-844 12 22 of of ADP cana-844 12 23 glioblastomas glioblastoma NOUN cana-844 12 24 . . PUNCT cana-844 13 1 keywords keyword NOUN cana-844 13 2 : : PUNCT cana-844 13 3 brain brain NOUN cana-844 13 4 tumor tumor NOUN cana-844 13 5 ; ; PUNCT cana-844 13 6 radiogenomic radiogenomic ADJ cana-844 13 7 ; ; PUNCT cana-844 13 8 classification classification NOUN cana-844 13 9 ; ; PUNCT cana-844 13 10 mgmt mgmt NOUN cana-844 13 11 promoter promoter NOUN cana-844 13 12 methylation methylation NOUN cana-844 13 13 ; ; PUNCT cana-844 13 14 magnetic magnetic ADJ cana-844 13 15 resonance resonance NOUN cana-844 13 16 imaging imaging NOUN cana-844 13 17 ( ( PUNCT cana-844 13 18 mri mri NOUN cana-844 13 19 ) ) PUNCT cana-844 13 20 . . PUNCT cana-844 14 1 1 1 X cana-844 14 2 . . X cana-844 14 3 introduction introduction NOUN cana-844 14 4 glioblastomas glioblastoma NOUN cana-844 14 5 ( ( PUNCT cana-844 14 6 gbms gbms PROPN cana-844 14 7 ) ) PUNCT cana-844 14 8 are be AUX cana-844 14 9 aggressive aggressive ADJ cana-844 14 10 brain brain NOUN cana-844 14 11 tumors tumor NOUN cana-844 14 12 that that PRON cana-844 14 13 spread spread VERB cana-844 14 14 extensively extensively ADV cana-844 14 15 and and CCONJ cana-844 14 16 are be AUX cana-844 14 17 resistant resistant ADJ cana-844 14 18 to to ADP cana-844 14 19 chemotherapy chemotherapy NOUN cana-844 14 20 . . PUNCT cana-844 15 1 they they PRON cana-844 15 2 often often ADV cana-844 15 3 come come VERB cana-844 15 4 back back ADV cana-844 15 5 after after ADP cana-844 15 6 surgery surgery NOUN cana-844 15 7 [ [ X cana-844 15 8 1 1 NUM cana-844 15 9 ] ] PUNCT cana-844 15 10 . . PUNCT cana-844 16 1 studies study NOUN cana-844 16 2 have have AUX cana-844 16 3 shown show VERB cana-844 16 4 that that DET cana-844 16 5 methylation methylation NOUN cana-844 16 6 of of ADP cana-844 16 7 the the DET cana-844 16 8 mgmt mgmt PROPN cana-844 16 9 gene gene NOUN cana-844 16 10 promoter promoter NOUN cana-844 16 11 , , PUNCT cana-844 16 12 found find VERB cana-844 16 13 in in ADP cana-844 16 14 30 30 NUM cana-844 16 15 - - SYM cana-844 16 16 60 60 NUM cana-844 16 17 % % NOUN cana-844 16 18 of of ADP cana-844 16 19 glioblastomas glioblastoma NOUN cana-844 16 20 , , PUNCT cana-844 16 21 can can AUX cana-844 16 22 improve improve VERB cana-844 16 23 the the DET cana-844 16 24 response response NOUN cana-844 16 25 to to ADP cana-844 16 26 tmz tmz PROPN cana-844 16 27 . . PUNCT cana-844 17 1 this this DET cana-844 17 2 methylation methylation NOUN cana-844 17 3 status status NOUN cana-844 17 4 is be AUX cana-844 17 5 an an DET cana-844 17 6 important important ADJ cana-844 17 7 biomarker biomarker NOUN cana-844 17 8 for for ADP cana-844 17 9 predicting predict VERB cana-844 17 10 outcomes outcome NOUN cana-844 17 11 in in ADP cana-844 17 12 gbm gbm NOUN cana-844 17 13 patients patient NOUN cana-844 17 14 [ [ X cana-844 17 15 2 2 NUM cana-844 17 16 ] ] PUNCT cana-844 17 17 . . PUNCT cana-844 18 1 currently currently ADV cana-844 18 2 , , PUNCT cana-844 18 3 the the DET cana-844 18 4 only only ADJ cana-844 18 5 way way NOUN cana-844 18 6 to to PART cana-844 18 7 determine determine VERB cana-844 18 8 mgmt mgmt NOUN cana-844 18 9 promoter promoter NOUN cana-844 18 10 methylation methylation NOUN cana-844 18 11 is be AUX cana-844 18 12 through through ADP cana-844 18 13 invasive invasive ADJ cana-844 18 14 brain brain NOUN cana-844 18 15 biopsy biopsy NOUN cana-844 18 16 or or CCONJ cana-844 18 17 surgical surgical ADJ cana-844 18 18 resection resection NOUN cana-844 18 19 [ [ X cana-844 18 20 3 3 NUM cana-844 18 21 ] ] PUNCT cana-844 18 22 . . PUNCT cana-844 19 1 significant significant ADJ cana-844 19 2 focus focus NOUN cana-844 19 3 has have AUX cana-844 19 4 been be AUX cana-844 19 5 placed place VERB cana-844 19 6 on on ADP cana-844 19 7 creating create VERB cana-844 19 8 non non ADJ cana-844 19 9 - - ADJ cana-844 19 10 invasive invasive ADJ cana-844 19 11 diagnostic diagnostic ADJ cana-844 19 12 techniques technique NOUN cana-844 19 13 using use VERB cana-844 19 14 images image NOUN cana-844 19 15 to to PART cana-844 19 16 identify identify VERB cana-844 19 17 mgmt mgmt ADJ cana-844 19 18 promoter promoter NOUN cana-844 19 19 methylation methylation NOUN cana-844 19 20 status status NOUN cana-844 19 21 for for ADP cana-844 19 22 glioblastoma glioblastoma NOUN cana-844 19 23 [ [ X cana-844 19 24 4 4 NUM cana-844 19 25 ] ] PUNCT cana-844 19 26 . . PUNCT cana-844 20 1 radiogenomics radiogenomic NOUN cana-844 20 2 combines combine VERB cana-844 20 3 communications communication NOUN cana-844 20 4 on on ADP cana-844 20 5 applied apply VERB cana-844 20 6 nonlinear nonlinear ADJ cana-844 20 7 analysis analysis NOUN cana-844 20 8 issn issn NOUN cana-844 20 9 : : PUNCT cana-844 20 10 1074 1074 NUM cana-844 20 11 - - PUNCT cana-844 20 12 133x 133x NUM cana-844 20 13 vol vol NOUN cana-844 20 14 31 31 NUM cana-844 20 15 no no NOUN cana-844 20 16 . . PUNCT cana-844 21 1 4s 4s NUM cana-844 21 2 ( ( PUNCT cana-844 21 3 2024 2024 NUM cana-844 21 4 ) ) PUNCT cana-844 21 5 230 230 NUM cana-844 21 6 https://internationalpubls.com https://internationalpubls.com X cana-844 21 7 radiological radiological ADJ cana-844 21 8 imaging imaging NOUN cana-844 21 9 with with ADP cana-844 21 10 genomic genomic ADJ cana-844 21 11 data datum NOUN cana-844 21 12 to to PART cana-844 21 13 potentially potentially ADV cana-844 21 14 characterize characterize VERB cana-844 21 15 gliomas glioma NOUN cana-844 21 16 and and CCONJ cana-844 21 17 predict predict VERB cana-844 21 18 molecular molecular ADJ cana-844 21 19 markers marker NOUN cana-844 21 20 without without ADP cana-844 21 21 invasive invasive ADJ cana-844 21 22 procedures procedure NOUN cana-844 21 23 . . PUNCT cana-844 22 1 the the DET cana-844 22 2 rsna rsna NOUN cana-844 22 3 - - PUNCT cana-844 22 4 miccai miccai PROPN cana-844 22 5 brain brain NOUN cana-844 22 6 tumor tumor NOUN cana-844 22 7 radiogenomic radiogenomic ADJ cana-844 22 8 classification classification NOUN cana-844 22 9 challenge challenge NOUN cana-844 22 10 is be AUX cana-844 22 11 at at ADP cana-844 22 12 the the DET cana-844 22 13 forefront forefront NOUN cana-844 22 14 of of ADP cana-844 22 15 using use VERB cana-844 22 16 deep deep ADJ cana-844 22 17 learning learning NOUN cana-844 22 18 and and CCONJ cana-844 22 19 machine machine NOUN cana-844 22 20 learning learn VERB cana-844 22 21 to to PART cana-844 22 22 predict predict VERB cana-844 22 23 mgmt mgmt PROPN cana-844 22 24 promoter promoter NOUN cana-844 22 25 methylation methylation NOUN cana-844 22 26 status status NOUN cana-844 22 27 from from ADP cana-844 22 28 imaging imaging NOUN cana-844 22 29 data datum NOUN cana-844 22 30 . . PUNCT cana-844 23 1 the the DET cana-844 23 2 challenge challenge NOUN cana-844 23 3 lies lie VERB cana-844 23 4 in in ADP cana-844 23 5 predicting predict VERB cana-844 23 6 mgmt mgmt ADJ cana-844 23 7 promoter promoter NOUN cana-844 23 8 methylation methylation NOUN cana-844 23 9 status status NOUN cana-844 23 10 in in ADP cana-844 23 11 gliomas glioma NOUN cana-844 23 12 due due ADP cana-844 23 13 to to ADP cana-844 23 14 the the DET cana-844 23 15 intricate intricate ADJ cana-844 23 16 relationship relationship NOUN cana-844 23 17 between between ADP cana-844 23 18 molecular molecular ADJ cana-844 23 19 characteristics characteristic NOUN cana-844 23 20 and and CCONJ cana-844 23 21 radiological radiological ADJ cana-844 23 22 features feature NOUN cana-844 23 23 . . PUNCT cana-844 24 1 addressing address VERB cana-844 24 2 multiple multiple ADJ cana-844 24 3 challenges challenge NOUN cana-844 24 4 is be AUX cana-844 24 5 necessary necessary ADJ cana-844 24 6 to to PART cana-844 24 7 integrate integrate VERB cana-844 24 8 radiomics radiomic NOUN cana-844 24 9 and and CCONJ cana-844 24 10 genomes genome NOUN cana-844 24 11 for for ADP cana-844 24 12 an an DET cana-844 24 13 in in ADP cana-844 24 14 - - PUNCT cana-844 24 15 depth depth NOUN cana-844 24 16 knowledge knowledge NOUN cana-844 24 17 of of ADP cana-844 24 18 tumour tumour NOUN cana-844 24 19 biology biology NOUN cana-844 24 20 and and CCONJ cana-844 24 21 individualised individualised ADJ cana-844 24 22 treatment treatment NOUN cana-844 24 23 plans plan NOUN cana-844 24 24 in in ADP cana-844 24 25 precision precision NOUN cana-844 24 26 healthcare healthcare NOUN cana-844 24 27 . . PUNCT cana-844 25 1 utilising utilise VERB cana-844 25 2 noninvasive noninvasive ADJ cana-844 25 3 imaging imaging NOUN cana-844 25 4 information information NOUN cana-844 25 5 for for ADP cana-844 25 6 radiogenomic radiogenomic ADJ cana-844 25 7 classification classification NOUN cana-844 25 8 expedites expedite VERB cana-844 25 9 the the DET cana-844 25 10 procedure procedure NOUN cana-844 25 11 , , PUNCT cana-844 25 12 lowering lower VERB cana-844 25 13 operational operational ADJ cana-844 25 14 concerns concern NOUN cana-844 25 15 and and CCONJ cana-844 25 16 suffering suffer VERB cana-844 25 17 among among ADP cana-844 25 18 patients patient NOUN cana-844 25 19 while while SCONJ cana-844 25 20 allowing allow VERB cana-844 25 21 for for ADP cana-844 25 22 real real ADJ cana-844 25 23 - - PUNCT cana-844 25 24 time time NOUN cana-844 25 25 tumour tumour NOUN cana-844 25 26 progression progression NOUN cana-844 25 27 and and CCONJ cana-844 25 28 treatment treatment NOUN cana-844 25 29 outcome outcome NOUN cana-844 25 30 tracking tracking NOUN cana-844 25 31 . . PUNCT cana-844 26 1 the the DET cana-844 26 2 multidimensional multidimensional ADJ cana-844 26 3 feature feature NOUN cana-844 26 4 spaces space NOUN cana-844 26 5 present present ADJ cana-844 26 6 in in ADP cana-844 26 7 the the DET cana-844 26 8 genetic genetic ADJ cana-844 26 9 information information NOUN cana-844 26 10 , , PUNCT cana-844 26 11 however however ADV cana-844 26 12 , , PUNCT cana-844 26 13 make make VERB cana-844 26 14 feature feature NOUN cana-844 26 15 selection selection NOUN cana-844 26 16 and and CCONJ cana-844 26 17 reduction reduction NOUN cana-844 26 18 of of ADP cana-844 26 19 dimensionality dimensionality NOUN cana-844 26 20 difficult difficult ADJ cana-844 26 21 , , PUNCT cana-844 26 22 especially especially ADV cana-844 26 23 when when SCONJ cana-844 26 24 trying try VERB cana-844 26 25 to to PART cana-844 26 26 find find VERB cana-844 26 27 meaningful meaningful ADJ cana-844 26 28 features feature NOUN cana-844 26 29 that that PRON cana-844 26 30 accurately accurately ADV cana-844 26 31 reflect reflect VERB cana-844 26 32 the the DET cana-844 26 33 methylation methylation NOUN cana-844 26 34 status status NOUN cana-844 26 35 of of ADP cana-844 26 36 the the DET cana-844 26 37 mgmt mgmt NOUN cana-844 26 38 promoter promoter NOUN cana-844 26 39 without without ADP cana-844 26 40 overfitting overfitte VERB cana-844 26 41 . . PUNCT cana-844 27 1 to to PART cana-844 27 2 avoid avoid VERB cana-844 27 3 bias bias NOUN cana-844 27 4 towards towards ADP cana-844 27 5 the the DET cana-844 27 6 majority majority NOUN cana-844 27 7 class class NOUN cana-844 27 8 , , PUNCT cana-844 27 9 it it PRON cana-844 27 10 is be AUX cana-844 27 11 essential essential ADJ cana-844 27 12 to to PART cana-844 27 13 deal deal VERB cana-844 27 14 with with ADP cana-844 27 15 inconsistencies inconsistency NOUN cana-844 27 16 in in ADP cana-844 27 17 the the DET cana-844 27 18 distribution distribution NOUN cana-844 27 19 of of ADP cana-844 27 20 methylation methylation NOUN cana-844 27 21 versus versus ADP cana-844 27 22 unmethylated unmethylated ADJ cana-844 27 23 mgmt mgmt NOUN cana-844 27 24 promoter promoter NOUN cana-844 27 25 labelling labelling NOUN cana-844 27 26 within within ADP cana-844 27 27 datasets dataset NOUN cana-844 27 28 . . PUNCT cana-844 28 1 employing employ VERB cana-844 28 2 both both PRON cana-844 28 3 machine machine NOUN cana-844 28 4 learning learning NOUN cana-844 28 5 and and CCONJ cana-844 28 6 techniques technique NOUN cana-844 28 7 from from ADP cana-844 28 8 deep deep ADJ cana-844 28 9 learning learning NOUN cana-844 28 10 , , PUNCT cana-844 28 11 the the DET cana-844 28 12 goal goal NOUN cana-844 28 13 is be AUX cana-844 28 14 to to PART cana-844 28 15 create create VERB cana-844 28 16 a a DET cana-844 28 17 reliable reliable ADJ cana-844 28 18 model model NOUN cana-844 28 19 for for ADP cana-844 28 20 prediction prediction NOUN cana-844 28 21 that that PRON cana-844 28 22 can can AUX cana-844 28 23 be be AUX cana-844 28 24 used use VERB cana-844 28 25 to to PART cana-844 28 26 identify identify VERB cana-844 28 27 the the DET cana-844 28 28 mgmt mgmt PROPN cana-844 28 29 promoter promoter NOUN cana-844 28 30 methylation methylation NOUN cana-844 28 31 status status NOUN cana-844 28 32 of of ADP cana-844 28 33 gliomas glioma NOUN cana-844 28 34 based base VERB cana-844 28 35 on on ADP cana-844 28 36 radiological radiological ADJ cana-844 28 37 imaging imaging NOUN cana-844 28 38 characteristics characteristic NOUN cana-844 28 39 taken take VERB cana-844 28 40 from from ADP cana-844 28 41 mri mri NOUN cana-844 28 42 images image NOUN cana-844 28 43 . . PUNCT cana-844 29 1 by by ADP cana-844 29 2 assuring assure VERB cana-844 29 3 its its PRON cana-844 29 4 capacity capacity NOUN cana-844 29 5 to to PART cana-844 29 6 generalise generalise VERB cana-844 29 7 across across ADP cana-844 29 8 a a DET cana-844 29 9 variety variety NOUN cana-844 29 10 of of ADP cana-844 29 11 patient patient ADJ cana-844 29 12 populations population NOUN cana-844 29 13 , , PUNCT cana-844 29 14 this this DET cana-844 29 15 approach approach NOUN cana-844 29 16 will will AUX cana-844 29 17 deal deal VERB cana-844 29 18 with with ADP cana-844 29 19 the the DET cana-844 29 20 innate innate ADJ cana-844 29 21 biological biological ADJ cana-844 29 22 diversity diversity NOUN cana-844 29 23 and and CCONJ cana-844 29 24 heterogenity heterogenity NOUN cana-844 29 25 of of ADP cana-844 29 26 brain brain NOUN cana-844 29 27 tumours tumour NOUN cana-844 29 28 , , PUNCT cana-844 29 29 including include VERB cana-844 29 30 mgmt mgmt NOUN cana-844 29 31 promoter promoter NOUN cana-844 29 32 methylation methylation NOUN cana-844 29 33 , , PUNCT cana-844 29 34 and and CCONJ cana-844 29 35 hence hence ADV cana-844 29 36 improve improve VERB cana-844 29 37 the the DET cana-844 29 38 accuracy accuracy NOUN cana-844 29 39 of of ADP cana-844 29 40 predictions prediction NOUN cana-844 29 41 . . PUNCT cana-844 30 1 harmonised harmonise VERB cana-844 30 2 preprocessing preprocessing NOUN cana-844 30 3 approaches approach NOUN cana-844 30 4 will will AUX cana-844 30 5 enable enable VERB cana-844 30 6 successful successful ADJ cana-844 30 7 fusion fusion NOUN cana-844 30 8 by by ADP cana-844 30 9 integrating integrate VERB cana-844 30 10 mri mri NOUN cana-844 30 11 and and CCONJ cana-844 30 12 genomic genomic ADJ cana-844 30 13 data datum NOUN cana-844 30 14 from from ADP cana-844 30 15 various various ADJ cana-844 30 16 sources source NOUN cana-844 30 17 . . PUNCT cana-844 31 1 in in ADP cana-844 31 2 addition addition NOUN cana-844 31 3 , , PUNCT cana-844 31 4 the the DET cana-844 31 5 goal goal NOUN cana-844 31 6 encompasses encompass VERB cana-844 31 7 finding find VERB cana-844 31 8 and and CCONJ cana-844 31 9 selecting select VERB cana-844 31 10 significant significant ADJ cana-844 31 11 radiomic radiomic ADJ cana-844 31 12 characteristics characteristic NOUN cana-844 31 13 linked link VERB cana-844 31 14 to to ADP cana-844 31 15 glioma glioma NOUN cana-844 31 16 mgmt mgmt NOUN cana-844 31 17 promoter promoter NOUN cana-844 31 18 methylation methylation NOUN cana-844 31 19 status status NOUN cana-844 31 20 . . PUNCT cana-844 32 1 in in ADP cana-844 32 2 order order NOUN cana-844 32 3 to to PART cana-844 32 4 determine determine VERB cana-844 32 5 the the DET cana-844 32 6 highest highest ADV cana-844 32 7 - - PUNCT cana-844 32 8 performing perform VERB cana-844 32 9 strategy strategy NOUN cana-844 32 10 , , PUNCT cana-844 32 11 the the DET cana-844 32 12 performance performance NOUN cana-844 32 13 of of ADP cana-844 32 14 several several ADJ cana-844 32 15 algorithms algorithm NOUN cana-844 32 16 based base VERB cana-844 32 17 on on ADP cana-844 32 18 deep deep ADJ cana-844 32 19 learning learning NOUN cana-844 32 20 and and CCONJ cana-844 32 21 machine machine NOUN cana-844 32 22 learning learn VERB cana-844 32 23 to to PART cana-844 32 24 predict predict VERB cana-844 32 25 the the DET cana-844 32 26 mgmt mgmt PROPN cana-844 32 27 promoter promoter NOUN cana-844 32 28 methylation methylation NOUN cana-844 32 29 status status NOUN cana-844 32 30 in in ADP cana-844 32 31 gliomas glioma NOUN cana-844 32 32 will will AUX cana-844 32 33 be be AUX cana-844 32 34 contrasted contrast VERB cana-844 32 35 at at ADP cana-844 32 36 the the DET cana-844 32 37 final final ADJ cana-844 32 38 stage stage NOUN cana-844 32 39 . . PUNCT cana-844 33 1 convolution convolution NOUN cana-844 33 2 is be AUX cana-844 33 3 a a DET cana-844 33 4 fundamental fundamental ADJ cana-844 33 5 operation operation NOUN cana-844 33 6 in in ADP cana-844 33 7 the the DET cana-844 33 8 field field NOUN cana-844 33 9 of of ADP cana-844 33 10 image image NOUN cana-844 33 11 processing processing NOUN cana-844 33 12 , , PUNCT cana-844 33 13 particularly particularly ADV cana-844 33 14 within within ADP cana-844 33 15 cnn cnn PROPN cana-844 33 16 architectures architecture NOUN cana-844 33 17 like like ADP cana-844 33 18 vgg19 vgg19 PROPN cana-844 33 19 and and CCONJ cana-844 33 20 resnet50 resnet50 NOUN cana-844 33 21 used use VERB cana-844 33 22 in in ADP cana-844 33 23 your your PRON cana-844 33 24 study study NOUN cana-844 33 25 . . PUNCT cana-844 34 1 the the DET cana-844 34 2 operation operation NOUN cana-844 34 3 involves involve VERB cana-844 34 4 sliding slide VERB cana-844 34 5 a a DET cana-844 34 6 kernel kernel NOUN cana-844 34 7 kkk kkk PROPN cana-844 34 8 over over ADP cana-844 34 9 the the DET cana-844 34 10 input input NOUN cana-844 34 11 image image PROPN cana-844 34 12 iii iii PROPN cana-844 34 13 , , PUNCT cana-844 34 14 calculating calculate VERB cana-844 34 15 the the DET cana-844 34 16 dot dot NOUN cana-844 34 17 product product NOUN cana-844 34 18 at at ADP cana-844 34 19 each each DET cana-844 34 20 position position NOUN cana-844 34 21 . . PUNCT cana-844 35 1 this this DET cana-844 35 2 operation operation NOUN cana-844 35 3 extracts extract VERB cana-844 35 4 local local ADJ cana-844 35 5 feature feature NOUN cana-844 35 6 representations representation NOUN cana-844 35 7 which which PRON cana-844 35 8 are be AUX cana-844 35 9 essential essential ADJ cana-844 35 10 for for ADP cana-844 35 11 learning learn VERB cana-844 35 12 image image NOUN cana-844 35 13 characteristics characteristic NOUN cana-844 35 14 relevant relevant ADJ cana-844 35 15 to to ADP cana-844 35 16 identifying identify VERB cana-844 35 17 radiological radiological ADJ cana-844 35 18 signatures signature NOUN cana-844 35 19 associated associate VERB cana-844 35 20 with with ADP cana-844 35 21 mgmt mgmt PROPN cana-844 35 22 methylation methylation PROPN cana-844 35 23 status status NOUN cana-844 35 24 . . PUNCT cana-844 36 1 convolution convolution NOUN cana-844 36 2 operation operation NOUN cana-844 36 3 : : PUNCT cana-844 36 4 𝑓(π‘₯ 𝑓(π‘₯ NOUN cana-844 36 5 , , PUNCT cana-844 36 6 𝑦 𝑦 NOUN cana-844 36 7 ) ) PUNCT cana-844 36 8 βˆ’ βˆ’ PROPN cana-844 37 1 ( ( PUNCT cana-844 37 2 𝐼 𝐼 PROPN cana-844 37 3 βˆ— βˆ— NOUN cana-844 37 4 𝐾)(π‘₯ 𝐾)(π‘₯ PROPN cana-844 37 5 , , PUNCT cana-844 37 6 𝑦 𝑦 NOUN cana-844 37 7 ) ) PUNCT cana-844 37 8 βˆ’ βˆ’ NOUN cana-844 37 9 βˆ‘ βˆ‘ PUNCT cana-844 37 10 β€Š β€Š SPACE cana-844 37 11 π‘Ž π‘Ž X cana-844 37 12 π‘–βˆ’βˆ’π‘Ž π‘–βˆ’βˆ’π‘Ž PRON cana-844 37 13 βˆ‘ βˆ‘ PART cana-844 37 14 β€Š β€Š SPACE cana-844 37 15 𝑏 𝑏 PROPN cana-844 37 16 π‘—βˆ’βˆ’π‘ π‘—βˆ’βˆ’π‘ PUNCT cana-844 37 17 𝐼(π‘₯ 𝐼(π‘₯ X cana-844 37 18 βˆ’ βˆ’ PROPN cana-844 37 19 𝑖 𝑖 SYM cana-844 37 20 , , PUNCT cana-844 37 21 𝑦 𝑦 NOUN cana-844 37 22 βˆ’ βˆ’ PROPN cana-844 37 23 𝑗)𝐾(𝑖 𝑗)𝐾(𝑖 PROPN cana-844 37 24 , , PUNCT cana-844 37 25 𝑗 𝑗 NOUN cana-844 37 26 ) ) PUNCT cana-844 37 27 ( ( PUNCT cana-844 37 28 1 1 X cana-844 37 29 ) ) PUNCT cana-844 37 30 the the DET cana-844 37 31 relu relu NOUN cana-844 37 32 function function NOUN cana-844 37 33 introduces introduce VERB cana-844 37 34 non non ADJ cana-844 37 35 - - ADJ cana-844 37 36 linearity linearity ADJ cana-844 37 37 to to ADP cana-844 37 38 the the DET cana-844 37 39 network network NOUN cana-844 37 40 , , PUNCT cana-844 37 41 which which PRON cana-844 37 42 is be AUX cana-844 37 43 crucial crucial ADJ cana-844 37 44 for for ADP cana-844 37 45 learning learn VERB cana-844 37 46 complex complex ADJ cana-844 37 47 patterns pattern NOUN cana-844 37 48 in in ADP cana-844 37 49 the the DET cana-844 37 50 data datum NOUN cana-844 37 51 . . PUNCT cana-844 38 1 in in ADP cana-844 38 2 the the DET cana-844 38 3 context context NOUN cana-844 38 4 of of ADP cana-844 38 5 neural neural ADJ cana-844 38 6 networks network NOUN cana-844 38 7 processing process VERB cana-844 38 8 radiogenomic radiogenomic ADJ cana-844 38 9 data datum NOUN cana-844 38 10 , , PUNCT cana-844 38 11 relu relu NOUN cana-844 38 12 helps help VERB cana-844 38 13 in in ADP cana-844 38 14 stabilizing stabilize VERB cana-844 38 15 the the DET cana-844 38 16 learning learning NOUN cana-844 38 17 and and CCONJ cana-844 38 18 overcoming overcome VERB cana-844 38 19 the the DET cana-844 38 20 vanishing vanish VERB cana-844 38 21 gradient gradient NOUN cana-844 38 22 problem problem NOUN cana-844 38 23 , , PUNCT cana-844 38 24 which which PRON cana-844 38 25 is be AUX cana-844 38 26 critical critical ADJ cana-844 38 27 when when SCONJ cana-844 38 28 training training NOUN cana-844 38 29 deep deep ADJ cana-844 38 30 neural neural ADJ cana-844 38 31 networks network NOUN cana-844 38 32 on on ADP cana-844 38 33 complex complex ADJ cana-844 38 34 medical medical ADJ cana-844 38 35 imaging imaging NOUN cana-844 38 36 data datum NOUN cana-844 38 37 . . PUNCT cana-844 39 1 communications communication NOUN cana-844 39 2 on on ADP cana-844 39 3 applied apply VERB cana-844 39 4 nonlinear nonlinear ADJ cana-844 39 5 analysis analysis NOUN cana-844 39 6 issn issn NOUN cana-844 39 7 : : PUNCT cana-844 39 8 1074 1074 NUM cana-844 39 9 - - PUNCT cana-844 39 10 133x 133x NUM cana-844 39 11 vol vol NOUN cana-844 39 12 31 31 NUM cana-844 39 13 no no NOUN cana-844 39 14 . . PUNCT cana-844 40 1 4s 4s NUM cana-844 40 2 ( ( PUNCT cana-844 40 3 2024 2024 NUM cana-844 40 4 ) ) PUNCT cana-844 40 5 231 231 NUM cana-844 40 6 https://internationalpubls.com https://internationalpubls.com X cana-844 40 7 relu relu NOUN cana-844 40 8 activation activation NOUN cana-844 40 9 function function NOUN cana-844 40 10 : : PUNCT cana-844 40 11 𝑔(𝑧 𝑔(𝑧 X cana-844 40 12 ) ) PUNCT cana-844 40 13 βˆ’ βˆ’ NOUN cana-844 40 14 max(0 max(0 NOUN cana-844 40 15 , , PUNCT cana-844 40 16 𝑧 𝑧 NOUN cana-844 40 17 ) ) PUNCT cana-844 40 18 ( ( PUNCT cana-844 40 19 2 2 X cana-844 40 20 ) ) PUNCT cana-844 40 21 this this DET cana-844 40 22 loss loss NOUN cana-844 40 23 function function NOUN cana-844 40 24 measures measure VERB cana-844 40 25 the the DET cana-844 40 26 discrepancy discrepancy NOUN cana-844 40 27 between between ADP cana-844 40 28 the the DET cana-844 40 29 predicted predict VERB cana-844 40 30 probabilities probability NOUN cana-844 40 31 and and CCONJ cana-844 40 32 the the DET cana-844 40 33 actual actual ADJ cana-844 40 34 labels label NOUN cana-844 40 35 . . PUNCT cana-844 41 1 it it PRON cana-844 41 2 is be AUX cana-844 41 3 particularly particularly ADV cana-844 41 4 effective effective ADJ cana-844 41 5 for for ADP cana-844 41 6 classification classification NOUN cana-844 41 7 problems problem NOUN cana-844 41 8 , , PUNCT cana-844 41 9 providing provide VERB cana-844 41 10 a a DET cana-844 41 11 robust robust ADJ cana-844 41 12 metric metric NOUN cana-844 41 13 for for ADP cana-844 41 14 optimizing optimize VERB cana-844 41 15 the the DET cana-844 41 16 neural neural ADJ cana-844 41 17 network network NOUN cana-844 41 18 in in ADP cana-844 41 19 predicting predict VERB cana-844 41 20 the the DET cana-844 41 21 binary binary ADJ cana-844 41 22 methylation methylation NOUN cana-844 41 23 status status NOUN cana-844 41 24 of of ADP cana-844 41 25 the the DET cana-844 41 26 mgmt mgmt PROPN cana-844 41 27 promoter promoter NOUN cana-844 41 28 . . PUNCT cana-844 42 1 cross cross ADJ cana-844 42 2 - - ADJ cana-844 42 3 entropy entropy ADJ cana-844 42 4 loss loss NOUN cana-844 42 5 for for ADP cana-844 42 6 binary binary ADJ cana-844 42 7 classification classification NOUN cana-844 42 8 : : PUNCT cana-844 42 9 𝐿(𝑦 𝐿(𝑦 NOUN cana-844 42 10 , , PUNCT cana-844 42 11 οΏ½ οΏ½ NOUN cana-844 42 12 Μ‚ Μ‚ NOUN cana-844 42 13 οΏ½ οΏ½ NOUN cana-844 42 14 ) ) PUNCT cana-844 42 15 = = SYM cana-844 42 16 βˆ’βŒˆπ‘¦log⁑( βˆ’βŒˆπ‘¦log⁑( NUM cana-844 42 17 οΏ½ οΏ½ NOUN cana-844 42 18 Μ‚ Μ‚ NOUN cana-844 42 19 οΏ½ οΏ½ NOUN cana-844 42 20 ) ) PUNCT cana-844 42 21 + + CCONJ cana-844 42 22 ( ( PUNCT cana-844 42 23 1 1 NUM cana-844 42 24 βˆ’ βˆ’ PROPN cana-844 42 25 𝑦)log⁑(1 𝑦)log⁑(1 NUM cana-844 42 26 βˆ’ βˆ’ PROPN cana-844 42 27 οΏ½ οΏ½ PROPN cana-844 42 28 Μ‚ Μ‚ NOUN cana-844 42 29 οΏ½ οΏ½ NOUN cana-844 42 30 ) ) PUNCT cana-844 42 31 ] ] PUNCT cana-844 43 1 ( ( PUNCT cana-844 43 2 3 3 X cana-844 43 3 ) ) PUNCT cana-844 43 4 gradient gradient ADJ cana-844 43 5 descent descent NOUN cana-844 43 6 is be AUX cana-844 43 7 a a DET cana-844 43 8 cornerstone cornerstone NOUN cana-844 43 9 optimization optimization NOUN cana-844 43 10 method method NOUN cana-844 43 11 used use VERB cana-844 43 12 to to PART cana-844 43 13 update update VERB cana-844 43 14 the the DET cana-844 43 15 weights weight NOUN cana-844 43 16 ΞΈ\thetaΞΈ ΞΈ\thetaΞΈ PROPN cana-844 43 17 in in ADP cana-844 43 18 neural neural ADJ cana-844 43 19 networks network NOUN cana-844 43 20 , , PUNCT cana-844 43 21 aiming aim VERB cana-844 43 22 to to PART cana-844 43 23 minimize minimize VERB cana-844 43 24 the the DET cana-844 43 25 loss loss NOUN cana-844 43 26 function function NOUN cana-844 43 27 j(ΞΈ)j(\theta)j(ΞΈ j(ΞΈ)j(\theta)j(ΞΈ PROPN cana-844 43 28 ) ) PUNCT cana-844 43 29 . . PUNCT cana-844 44 1 the the DET cana-844 44 2 learning learning NOUN cana-844 44 3 rate rate NOUN cana-844 44 4 Ξ·\etaΞ· Ξ·\etaΞ· NOUN cana-844 44 5 controls control VERB cana-844 44 6 the the DET cana-844 44 7 size size NOUN cana-844 44 8 of of ADP cana-844 44 9 the the DET cana-844 44 10 steps step NOUN cana-844 44 11 taken take VERB cana-844 44 12 towards towards ADP cana-844 44 13 the the DET cana-844 44 14 minimum minimum NOUN cana-844 44 15 of of ADP cana-844 44 16 jjj jjj NOUN cana-844 44 17 , , PUNCT cana-844 44 18 crucial crucial ADJ cana-844 44 19 for for ADP cana-844 44 20 effective effective ADJ cana-844 44 21 training training NOUN cana-844 44 22 of of ADP cana-844 44 23 models model NOUN cana-844 44 24 on on ADP cana-844 44 25 radiogenomic radiogenomic ADJ cana-844 44 26 data datum NOUN cana-844 44 27 . . PUNCT cana-844 45 1 gradient gradient ADJ cana-844 45 2 descent descent NOUN cana-844 45 3 : : PUNCT cana-844 45 4 πœƒnew πœƒnew ADJ cana-844 45 5 βˆ’ βˆ’ PROPN cana-844 45 6 πœƒodd πœƒodd NOUN cana-844 45 7 βˆ’ βˆ’ PROPN cana-844 45 8 πœ‚βˆ‡πœƒπ½(πœƒ πœ‚βˆ‡πœƒπ½(πœƒ NOUN cana-844 45 9 ) ) PUNCT cana-844 45 10 ( ( PUNCT cana-844 45 11 4 4 X cana-844 45 12 ) ) PUNCT cana-844 45 13 sgd sgd X cana-844 45 14 optimizes optimize VERB cana-844 45 15 the the DET cana-844 45 16 learning learning NOUN cana-844 45 17 process process NOUN cana-844 45 18 by by ADP cana-844 45 19 updating update VERB cana-844 45 20 the the DET cana-844 45 21 model model NOUN cana-844 45 22 parameters parameter NOUN cana-844 45 23 using use VERB cana-844 45 24 a a DET cana-844 45 25 randomly randomly ADV cana-844 45 26 selected select VERB cana-844 45 27 subset subset NOUN cana-844 45 28 of of ADP cana-844 45 29 the the DET cana-844 45 30 data datum NOUN cana-844 45 31 at at ADP cana-844 45 32 each each DET cana-844 45 33 iteration iteration NOUN cana-844 45 34 . . PUNCT cana-844 46 1 this this DET cana-844 46 2 approach approach NOUN cana-844 46 3 reduces reduce VERB cana-844 46 4 the the DET cana-844 46 5 computational computational ADJ cana-844 46 6 burden burden NOUN cana-844 46 7 and and CCONJ cana-844 46 8 can can AUX cana-844 46 9 lead lead VERB cana-844 46 10 to to ADP cana-844 46 11 faster fast ADJ cana-844 46 12 convergence convergence NOUN cana-844 46 13 , , PUNCT cana-844 46 14 especially especially ADV cana-844 46 15 beneficial beneficial ADJ cana-844 46 16 in in ADP cana-844 46 17 large large ADJ cana-844 46 18 datasets dataset NOUN cana-844 46 19 like like ADP cana-844 46 20 those those PRON cana-844 46 21 used use VERB cana-844 46 22 in in ADP cana-844 46 23 radiogenomic radiogenomic ADJ cana-844 46 24 studies study NOUN cana-844 46 25 . . PUNCT cana-844 47 1 stochastic stochastic ADJ cana-844 47 2 gradient gradient ADJ cana-844 47 3 descent descent NOUN cana-844 47 4 ( ( PUNCT cana-844 47 5 sgd sgd PROPN cana-844 47 6 ): ): PUNCT cana-844 47 7 πœƒ πœƒ NOUN cana-844 47 8 βˆ’ βˆ’ NOUN cana-844 47 9 πœƒ πœƒ NOUN cana-844 47 10 βˆ’ βˆ’ NOUN cana-844 47 11 πœ‚βˆ‡πœƒπ½(πœƒ πœ‚βˆ‡πœƒπ½(πœƒ NOUN cana-844 47 12 ; ; PUNCT cana-844 47 13 π‘₯ π‘₯ PRON cana-844 47 14 ( ( PUNCT cana-844 47 15 𝑖 𝑖 NOUN cana-844 47 16 ) ) PUNCT cana-844 47 17 , , PUNCT cana-844 47 18 𝑦(𝑖 𝑦(𝑖 NOUN cana-844 47 19 ) ) PUNCT cana-844 47 20 ) ) PUNCT cana-844 47 21 ( ( PUNCT cana-844 47 22 5 5 X cana-844 47 23 ) ) PUNCT cana-844 47 24 batch batch NOUN cana-844 47 25 normalization normalization NOUN cana-844 47 26 standardizes standardize VERB cana-844 47 27 the the DET cana-844 47 28 inputs input NOUN cana-844 47 29 of of ADP cana-844 47 30 each each DET cana-844 47 31 layer layer NOUN cana-844 47 32 within within ADP cana-844 47 33 the the DET cana-844 47 34 network network NOUN cana-844 47 35 to to PART cana-844 47 36 have have VERB cana-844 47 37 zero zero NUM cana-844 47 38 mean mean NOUN cana-844 47 39 and and CCONJ cana-844 47 40 unit unit NOUN cana-844 47 41 variance variance NOUN cana-844 47 42 . . PUNCT cana-844 48 1 this this DET cana-844 48 2 normalization normalization NOUN cana-844 48 3 helps help VERB cana-844 48 4 in in ADP cana-844 48 5 speeding speed VERB cana-844 48 6 up up ADP cana-844 48 7 the the DET cana-844 48 8 training training NOUN cana-844 48 9 process process NOUN cana-844 48 10 and and CCONJ cana-844 48 11 reducing reduce VERB cana-844 48 12 the the DET cana-844 48 13 internal internal ADJ cana-844 48 14 covariate covariate ADJ cana-844 48 15 shift shift NOUN cana-844 48 16 , , PUNCT cana-844 48 17 making make VERB cana-844 48 18 the the DET cana-844 48 19 network network NOUN cana-844 48 20 more more ADV cana-844 48 21 stable stable ADJ cana-844 48 22 and and CCONJ cana-844 48 23 efficient efficient ADJ cana-844 48 24 . . PUNCT cana-844 49 1 batch batch NOUN cana-844 49 2 normalization normalization NOUN cana-844 49 3 : : PUNCT cana-844 49 4 οΏ½ οΏ½ PROPN cana-844 49 5 Μ‚ Μ‚ SYM cana-844 49 6 οΏ½ οΏ½ NOUN cana-844 49 7 (π‘˜ (π‘˜ NOUN cana-844 49 8 ) ) PUNCT cana-844 50 1 βˆ’ βˆ’ PROPN cana-844 50 2 π‘₯(π‘˜)βˆ’πœ‡πœ‡ π‘₯(π‘˜)βˆ’πœ‡πœ‡ PROPN cana-844 50 3 βˆšπœŽπ‘› βˆšπœŽπ‘› PROPN cana-844 50 4 2+𝑒 2+𝑒 NUM cana-844 50 5 ( ( PUNCT cana-844 50 6 6 6 NUM cana-844 50 7 ) ) PUNCT cana-844 50 8 the the DET cana-844 50 9 exponential exponential NOUN cana-844 50 10 of of ADP cana-844 50 11 each each DET cana-844 50 12 output output NOUN cana-844 50 13 and and CCONJ cana-844 50 14 then then ADV cana-844 50 15 normalizing normalize VERB cana-844 50 16 these these DET cana-844 50 17 values value NOUN cana-844 50 18 by by ADP cana-844 50 19 the the DET cana-844 50 20 sum sum NOUN cana-844 50 21 of of ADP cana-844 50 22 all all DET cana-844 50 23 exponentials exponential NOUN cana-844 50 24 . . PUNCT cana-844 51 1 this this PRON cana-844 51 2 provides provide VERB cana-844 51 3 a a DET cana-844 51 4 probabilistic probabilistic ADJ cana-844 51 5 interpretation interpretation NOUN cana-844 51 6 of of ADP cana-844 51 7 the the DET cana-844 51 8 model model NOUN cana-844 51 9 's 's PART cana-844 51 10 outputs output NOUN cana-844 51 11 , , PUNCT cana-844 51 12 useful useful ADJ cana-844 51 13 for for ADP cana-844 51 14 the the DET cana-844 51 15 final final ADJ cana-844 51 16 classification classification NOUN cana-844 51 17 in in ADP cana-844 51 18 multilabel multilabel NOUN cana-844 51 19 tasks task NOUN cana-844 51 20 , , PUNCT cana-844 51 21 such such ADJ cana-844 51 22 as as ADP cana-844 51 23 differentiating differentiate VERB cana-844 51 24 between between ADP cana-844 51 25 various various ADJ cana-844 51 26 radiogenomic radiogenomic ADJ cana-844 51 27 features feature NOUN cana-844 51 28 softmax softmax NOUN cana-844 51 29 function function NOUN cana-844 51 30 : : PUNCT cana-844 51 31 𝜎(𝑧)𝑗 𝜎(𝑧)𝑗 NOUN cana-844 51 32 βˆ’ βˆ’ NOUN cana-844 51 33 𝑒𝑧 𝑒𝑧 INTJ cana-844 51 34 βˆ‘ βˆ‘ PROPN cana-844 51 35 β€Š β€Š SPACE cana-844 51 36 𝐾 𝐾 PROPN cana-844 52 1 π‘˜=1 π‘˜=1 PROPN cana-844 52 2 β€Š β€Š SPACE cana-844 52 3 𝑒 𝑒 PROPN cana-844 52 4 2 2 NUM cana-844 52 5 for for ADP cana-844 52 6 𝑗 𝑗 PRON cana-844 52 7 βˆ’ βˆ’ PROPN cana-844 52 8 1 1 NUM cana-844 52 9 , , PUNCT cana-844 52 10 … … PUNCT cana-844 52 11 , , PUNCT cana-844 52 12 𝐾 𝐾 PROPN cana-844 52 13 ( ( PUNCT cana-844 52 14 7 7 NUM cana-844 52 15 ) ) PUNCT cana-844 52 16 the the DET cana-844 52 17 exponential exponential NOUN cana-844 52 18 of of ADP cana-844 52 19 each each DET cana-844 52 20 output output NOUN cana-844 52 21 and and CCONJ cana-844 52 22 then then ADV cana-844 52 23 normalizing normalize VERB cana-844 52 24 these these DET cana-844 52 25 values value NOUN cana-844 52 26 by by ADP cana-844 52 27 the the DET cana-844 52 28 sum sum NOUN cana-844 52 29 of of ADP cana-844 52 30 all all DET cana-844 52 31 exponentials exponential NOUN cana-844 52 32 . . PUNCT cana-844 53 1 this this PRON cana-844 53 2 provides provide VERB cana-844 53 3 a a DET cana-844 53 4 probabilistic probabilistic ADJ cana-844 53 5 interpretation interpretation NOUN cana-844 53 6 of of ADP cana-844 53 7 the the DET cana-844 53 8 model model NOUN cana-844 53 9 's 's PART cana-844 53 10 outputs output NOUN cana-844 53 11 , , PUNCT cana-844 53 12 useful useful ADJ cana-844 53 13 for for ADP cana-844 53 14 the the DET cana-844 53 15 final final ADJ cana-844 53 16 classification classification NOUN cana-844 53 17 in in ADP cana-844 53 18 multilabel multilabel NOUN cana-844 53 19 tasks task NOUN cana-844 53 20 , , PUNCT cana-844 53 21 such such ADJ cana-844 53 22 as as ADP cana-844 53 23 differentiating differentiate VERB cana-844 53 24 between between ADP cana-844 53 25 various various ADJ cana-844 53 26 radiogenomic radiogenomic ADJ cana-844 53 27 features feature NOUN cana-844 53 28 communications communication NOUN cana-844 53 29 on on ADP cana-844 53 30 applied apply VERB cana-844 53 31 nonlinear nonlinear ADJ cana-844 53 32 analysis analysis NOUN cana-844 53 33 issn issn NOUN cana-844 53 34 : : PUNCT cana-844 53 35 1074 1074 NUM cana-844 53 36 - - PUNCT cana-844 53 37 133x 133x NUM cana-844 53 38 vol vol NOUN cana-844 53 39 31 31 NUM cana-844 53 40 no no NOUN cana-844 53 41 . . PUNCT cana-844 54 1 4s 4s NUM cana-844 54 2 ( ( PUNCT cana-844 54 3 2024 2024 NUM cana-844 54 4 ) ) PUNCT cana-844 54 5 232 232 NUM cana-844 55 1 https://internationalpubls.com https://internationalpubls.com X cana-844 55 2 logistic logistic ADJ cana-844 55 3 regression regression NOUN cana-844 55 4 model model NOUN cana-844 55 5 : : PUNCT cana-844 55 6 𝑝(𝑦 𝑝(𝑦 PROPN cana-844 55 7 βˆ’ βˆ’ PROPN cana-844 55 8 1 1 NUM cana-844 55 9 ∣ ∣ PROPN cana-844 55 10 π‘₯ π‘₯ NOUN cana-844 55 11 ) ) PUNCT cana-844 55 12 βˆ’ βˆ’ PROPN cana-844 56 1 1 1 NUM cana-844 56 2 1+π‘’βˆ’πœŽ 1+π‘’βˆ’πœŽ X cana-844 56 3 𝑇π‘₯ 𝑇π‘₯ PROPN cana-844 56 4 ( ( PUNCT cana-844 56 5 8) 8) NUM cana-844 56 6 k k ADV cana-844 56 7 - - PUNCT cana-844 56 8 nearest near ADJ cana-844 56 9 neighbours neighbour NOUN cana-844 56 10 ( ( PUNCT cana-844 56 11 knn knn PROPN cana-844 56 12 ) ) PUNCT cana-844 56 13 distance distance NOUN cana-844 56 14 metric metric NOUN cana-844 56 15 ( ( PUNCT cana-844 56 16 euclidean euclidean PROPN cana-844 56 17 ): ): PUNCT cana-844 56 18 knn knn PROPN cana-844 56 19 uses use VERB cana-844 56 20 this this DET cana-844 56 21 distance distance NOUN cana-844 56 22 metric metric ADJ cana-844 56 23 to to PART cana-844 56 24 find find VERB cana-844 56 25 the the DET cana-844 56 26 k k PROPN cana-844 56 27 closest close ADJ cana-844 56 28 training training NOUN cana-844 56 29 examples example NOUN cana-844 56 30 to to ADP cana-844 56 31 a a DET cana-844 56 32 new new ADJ cana-844 56 33 data data NOUN cana-844 56 34 point point NOUN cana-844 56 35 xβ€² xβ€² PROPN cana-844 57 1 classifying classify VERB cana-844 57 2 the the DET cana-844 57 3 point point NOUN cana-844 57 4 based base VERB cana-844 57 5 on on ADP cana-844 57 6 the the DET cana-844 57 7 majority majority NOUN cana-844 57 8 label label NOUN cana-844 57 9 of of ADP cana-844 57 10 these these DET cana-844 57 11 neighbours neighbour NOUN cana-844 57 12 . . PUNCT cana-844 58 1 this this DET cana-844 58 2 non non ADJ cana-844 58 3 - - ADJ cana-844 58 4 parametric parametric ADJ cana-844 58 5 method method NOUN cana-844 58 6 is be AUX cana-844 58 7 invaluable invaluable ADJ cana-844 58 8 for for ADP cana-844 58 9 capturing capture VERB cana-844 58 10 nonlinear nonlinear ADJ cana-844 58 11 relationships relationship NOUN cana-844 58 12 in in ADP cana-844 58 13 the the DET cana-844 58 14 data datum NOUN cana-844 58 15 without without ADP cana-844 58 16 assuming assume VERB cana-844 58 17 a a DET cana-844 58 18 specific specific ADJ cana-844 58 19 form form NOUN cana-844 58 20 for for ADP cana-844 58 21 the the DET cana-844 58 22 underlying underlie VERB cana-844 58 23 model model NOUN cana-844 58 24 . . PUNCT cana-844 59 1 𝑑(π‘₯ 𝑑(π‘₯ PROPN cana-844 59 2 , , PUNCT cana-844 59 3 π‘₯β€² π‘₯β€² NUM cana-844 59 4 ) ) PUNCT cana-844 60 1 βˆ’ βˆ’ ADP cana-844 60 2 βˆšβˆ‘ βˆšβˆ‘ VERB cana-844 60 3 β€Š β€Š SPACE cana-844 60 4 𝑛 𝑛 ADP cana-844 60 5 π‘–βˆ’1 π‘–βˆ’1 PROPN cana-844 60 6 β€Š β€Š SPACE cana-844 60 7 ( ( PUNCT cana-844 60 8 π‘₯𝑖 π‘₯𝑖 NUM cana-844 60 9 βˆ’ βˆ’ PROPN cana-844 61 1 π‘₯𝑖 π‘₯𝑖 X cana-844 61 2 β€²)2 β€²)2 X cana-844 61 3 ( ( PUNCT cana-844 61 4 9 9 NUM cana-844 61 5 ) ) PUNCT cana-844 61 6 naive naive ADJ cana-844 61 7 bayes bayes NOUN cana-844 61 8 classifier classifier NOUN cana-844 61 9 : : PUNCT cana-844 61 10 𝑃(𝑦 𝑃(𝑦 PROPN cana-844 61 11 ∣ ∣ PROPN cana-844 61 12 π‘₯1 π‘₯1 PROPN cana-844 61 13 , , PUNCT cana-844 61 14 … … PUNCT cana-844 61 15 , , PUNCT cana-844 61 16 π‘₯𝑛 π‘₯𝑛 NOUN cana-844 61 17 ) ) PUNCT cana-844 61 18 βˆ’ βˆ’ ADP cana-844 61 19 𝑃(𝑦)∏ 𝑃(𝑦)∏ INTJ cana-844 61 20 β€Š β€Š SPACE cana-844 61 21 𝑛 𝑛 PRON cana-844 61 22 𝑛 𝑛 PROPN cana-844 61 23 β€Š β€Š SPACE cana-844 61 24 , , PUNCT cana-844 61 25 𝑃(π‘₯1βˆ£π‘¦ 𝑃(π‘₯1βˆ£π‘¦ PROPN cana-844 61 26 ) ) PUNCT cana-844 61 27 𝑃𝑃(π‘₯1, 𝑃𝑃(π‘₯1, NUM cana-844 61 28 … … PUNCT cana-844 61 29 ,π‘₯𝑛 ,π‘₯𝑛 PUNCT cana-844 61 30 ) ) PUNCT cana-844 61 31 ( ( PUNCT cana-844 61 32 10 10 X cana-844 61 33 ) ) PUNCT cana-844 61 34 naive naive ADJ cana-844 61 35 bayes bayes NOUN cana-844 61 36 classifiers classifier NOUN cana-844 61 37 assume assume VERB cana-844 61 38 that that SCONJ cana-844 61 39 the the DET cana-844 61 40 features feature NOUN cana-844 61 41 are be AUX cana-844 61 42 conditionally conditionally ADV cana-844 61 43 independent independent ADJ cana-844 61 44 given give VERB cana-844 61 45 the the DET cana-844 61 46 target target NOUN cana-844 61 47 class class NOUN cana-844 61 48 y y PROPN cana-844 61 49 and and CCONJ cana-844 61 50 calculate calculate VERB cana-844 61 51 the the DET cana-844 61 52 posterior posterior ADJ cana-844 61 53 probability probability NOUN cana-844 61 54 of of ADP cana-844 61 55 y y PROPN cana-844 61 56 given give VERB cana-844 61 57 the the DET cana-844 61 58 features feature NOUN cana-844 61 59 . . PUNCT cana-844 62 1 this this DET cana-844 62 2 simplicity simplicity NOUN cana-844 62 3 and and CCONJ cana-844 62 4 efficiency efficiency NOUN cana-844 62 5 make make VERB cana-844 62 6 it it PRON cana-844 62 7 particularly particularly ADV cana-844 62 8 useful useful ADJ cana-844 62 9 for for ADP cana-844 62 10 initial initial ADJ cana-844 62 11 explorations exploration NOUN cana-844 62 12 and and CCONJ cana-844 62 13 baselines baseline NOUN cana-844 62 14 in in ADP cana-844 62 15 complex complex ADJ cana-844 62 16 predictive predictive ADJ cana-844 62 17 tasks task NOUN cana-844 62 18 involving involve VERB cana-844 62 19 highdimensional highdimensional ADJ cana-844 62 20 data datum NOUN cana-844 62 21 like like ADP cana-844 62 22 radio radio NOUN cana-844 62 23 genomics genomic NOUN cana-844 62 24 . . PUNCT cana-844 63 1 random random ADJ cana-844 63 2 forest forest NOUN cana-844 63 3 gini gini PROPN cana-844 63 4 impurity impurity NOUN cana-844 63 5 : : PUNCT cana-844 63 6 𝐼𝐺(𝑝 𝐼𝐺(𝑝 VERB cana-844 63 7 ) ) PUNCT cana-844 63 8 βˆ’ βˆ’ PROPN cana-844 63 9 1 1 NUM cana-844 63 10 βˆ’ βˆ’ NOUN cana-844 63 11 βˆ‘ βˆ‘ DET cana-844 63 12 β€Š β€Š SPACE cana-844 63 13 π‘˜ π‘˜ PROPN cana-844 63 14 π‘–βˆ’1 π‘–βˆ’1 PROPN cana-844 63 15 𝑝𝑖 𝑝𝑖 PROPN cana-844 63 16 2 2 NUM cana-844 63 17 ( ( PUNCT cana-844 63 18 11 11 NUM cana-844 63 19 ) ) PUNCT cana-844 63 20 gini gini NOUN cana-844 63 21 impurity impurity NOUN cana-844 63 22 is be AUX cana-844 63 23 used use VERB cana-844 63 24 within within ADP cana-844 63 25 the the DET cana-844 63 26 random random ADJ cana-844 63 27 forest forest NOUN cana-844 63 28 algorithm algorithm NOUN cana-844 63 29 to to PART cana-844 63 30 decide decide VERB cana-844 63 31 the the DET cana-844 63 32 best good ADJ cana-844 63 33 split split NOUN cana-844 63 34 at at ADP cana-844 63 35 each each DET cana-844 63 36 node node NOUN cana-844 63 37 of of ADP cana-844 63 38 the the DET cana-844 63 39 decision decision NOUN cana-844 63 40 trees tree NOUN cana-844 63 41 . . PUNCT cana-844 64 1 it it PRON cana-844 64 2 measures measure VERB cana-844 64 3 the the DET cana-844 64 4 impurity impurity NOUN cana-844 64 5 of of ADP cana-844 64 6 a a DET cana-844 64 7 node node NOUN cana-844 64 8 , , PUNCT cana-844 64 9 with with ADP cana-844 64 10 0 0 NUM cana-844 64 11 representing represent VERB cana-844 64 12 a a DET cana-844 64 13 perfectly perfectly ADV cana-844 64 14 pure pure ADJ cana-844 64 15 node node NOUN cana-844 64 16 . . PUNCT cana-844 65 1 minimizing minimize VERB cana-844 65 2 the the DET cana-844 65 3 gini gini PROPN cana-844 65 4 impurity impurity NOUN cana-844 65 5 helps help VERB cana-844 65 6 in in ADP cana-844 65 7 creating create VERB cana-844 65 8 more more ADV cana-844 65 9 accurate accurate ADJ cana-844 65 10 and and CCONJ cana-844 65 11 robust robust ADJ cana-844 65 12 decision decision NOUN cana-844 65 13 trees tree NOUN cana-844 65 14 by by ADP cana-844 65 15 ensuring ensure VERB cana-844 65 16 that that SCONJ cana-844 65 17 each each DET cana-844 65 18 node node NOUN cana-844 65 19 splits split VERB cana-844 65 20 the the DET cana-844 65 21 data datum NOUN cana-844 65 22 as as ADV cana-844 65 23 cleanly cleanly ADV cana-844 65 24 as as ADP cana-844 65 25 possible possible ADJ cana-844 65 26 , , PUNCT cana-844 65 27 which which PRON cana-844 65 28 is be AUX cana-844 65 29 crucial crucial ADJ cana-844 65 30 for for ADP cana-844 65 31 dealing deal VERB cana-844 65 32 with with ADP cana-844 65 33 the the DET cana-844 65 34 heterogeneity heterogeneity NOUN cana-844 65 35 of of ADP cana-844 65 36 radiogenomic radiogenomic ADJ cana-844 65 37 data datum NOUN cana-844 65 38 . . PUNCT cana-844 66 1 support support NOUN cana-844 66 2 vector vector NOUN cana-844 66 3 machine machine NOUN cana-844 66 4 ( ( PUNCT cana-844 66 5 svm svm ADJ cana-844 66 6 ) ) PUNCT cana-844 66 7 optimization optimization NOUN cana-844 66 8 : : PUNCT cana-844 66 9 min min PROPN cana-844 66 10 πœƒ πœƒ NOUN cana-844 66 11 β€Š β€Š SPACE cana-844 66 12 1 1 NUM cana-844 66 13 2 2 NUM cana-844 66 14 βˆ₯ βˆ₯ NUM cana-844 66 15 πœƒ πœƒ PUNCT cana-844 66 16 βˆ₯2 βˆ₯2 NOUN cana-844 66 17 + + CCONJ cana-844 66 18 𝐢 𝐢 PROPN cana-844 66 19 βˆ‘ βˆ‘ PUNCT cana-844 66 20 β€Š β€Š SPACE cana-844 66 21 π‘š π‘š PROPN cana-844 66 22 π‘–βˆ’1 π‘–βˆ’1 PROPN cana-844 66 23 max max PROPN cana-844 66 24 ( ( PUNCT cana-844 66 25 0,1 0,1 NUM cana-844 66 26 βˆ’ βˆ’ NOUN cana-844 66 27 𝑦(𝑖)(πœƒπ‘‡π‘₯(𝑖 𝑦(𝑖)(πœƒπ‘‡π‘₯(𝑖 NOUN cana-844 66 28 ) ) PUNCT cana-844 66 29 + + NOUN cana-844 66 30 𝑏 𝑏 NOUN cana-844 66 31 ) ) PUNCT cana-844 66 32 ) ) PUNCT cana-844 66 33 ( ( PUNCT cana-844 66 34 12 12 X cana-844 66 35 ) ) PUNCT cana-844 66 36 this this DET cana-844 66 37 formulation formulation NOUN cana-844 66 38 represents represent VERB cana-844 66 39 the the DET cana-844 66 40 optimization optimization NOUN cana-844 66 41 problem problem NOUN cana-844 66 42 for for ADP cana-844 66 43 training train VERB cana-844 66 44 an an DET cana-844 66 45 svm svm NOUN cana-844 66 46 with with ADP cana-844 66 47 a a DET cana-844 66 48 linear linear ADJ cana-844 66 49 kernel kernel NOUN cana-844 66 50 . . PUNCT cana-844 67 1 the the DET cana-844 67 2 first first ADJ cana-844 67 3 term term NOUN cana-844 67 4 regularizes regularize VERB cana-844 67 5 the the DET cana-844 67 6 model model NOUN cana-844 67 7 by by ADP cana-844 67 8 controlling control VERB cana-844 67 9 the the DET cana-844 67 10 magnitude magnitude NOUN cana-844 67 11 of of ADP cana-844 67 12 the the DET cana-844 67 13 weight weight NOUN cana-844 67 14 vector vector NOUN cana-844 67 15 ΞΈ ΞΈ NOUN cana-844 67 16 preventing prevent VERB cana-844 67 17 overfitting overfitting NOUN cana-844 67 18 . . PUNCT cana-844 68 1 the the DET cana-844 68 2 second second ADJ cana-844 68 3 term term NOUN cana-844 68 4 , , PUNCT cana-844 68 5 known know VERB cana-844 68 6 as as ADP cana-844 68 7 the the DET cana-844 68 8 hinge hinge NOUN cana-844 68 9 loss loss NOUN cana-844 68 10 , , PUNCT cana-844 68 11 penalizes penalize NOUN cana-844 68 12 misclassifications misclassification NOUN cana-844 68 13 . . PUNCT cana-844 69 1 c c PROPN cana-844 69 2 is be AUX cana-844 69 3 a a DET cana-844 69 4 hyperparameter hyperparameter NOUN cana-844 69 5 that that PRON cana-844 69 6 balances balance VERB cana-844 69 7 these these DET cana-844 69 8 two two NUM cana-844 69 9 aspects aspect NOUN cana-844 69 10 . . PUNCT cana-844 70 1 this this PRON cana-844 70 2 is be AUX cana-844 70 3 especially especially ADV cana-844 70 4 valuable valuable ADJ cana-844 70 5 in in ADP cana-844 70 6 radiogenomic radiogenomic ADJ cana-844 70 7 data datum NOUN cana-844 70 8 , , PUNCT cana-844 70 9 where where SCONJ cana-844 70 10 clear clear ADJ cana-844 70 11 margins margin NOUN cana-844 70 12 between between ADP cana-844 70 13 classes class NOUN cana-844 70 14 can can AUX cana-844 70 15 significantly significantly ADV cana-844 70 16 enhance enhance VERB cana-844 70 17 predictive predictive ADJ cana-844 70 18 performance performance NOUN cana-844 70 19 . . PUNCT cana-844 71 1 decision decision NOUN cana-844 71 2 tree tree NOUN cana-844 71 3 splitting splitting NOUN cana-844 71 4 criterion criterion NOUN cana-844 71 5 ( ( PUNCT cana-844 71 6 information information NOUN cana-844 71 7 gain gain NOUN cana-844 71 8 ): ): PUNCT cana-844 71 9 𝐼𝐺(𝑇 𝐼𝐺(𝑇 NOUN cana-844 71 10 , , PUNCT cana-844 71 11 π‘Ž π‘Ž NOUN cana-844 71 12 ) ) PUNCT cana-844 71 13 βˆ’ βˆ’ NOUN cana-844 71 14 𝐻(𝑇 𝐻(𝑇 NUM cana-844 71 15 ) ) PUNCT cana-844 71 16 βˆ’ βˆ’ PUNCT cana-844 71 17 βˆ‘ βˆ‘ PUNCT cana-844 71 18 β€Š β€Š SPACE cana-844 71 19 π‘£βˆˆvalues⁑(π‘Ž π‘£βˆˆvalues⁑(π‘Ž NUM cana-844 71 20 ) ) PUNCT cana-844 71 21 |π‘‡βˆ£| |π‘‡βˆ£| ADV cana-844 71 22 |𝑇| |𝑇| PROPN cana-844 71 23 𝐻(𝑇𝑣 𝐻(𝑇𝑣 NUM cana-844 71 24 ) ) PUNCT cana-844 71 25 ( ( PUNCT cana-844 71 26 13 13 NUM cana-844 71 27 ) ) PUNCT cana-844 71 28 information information NOUN cana-844 71 29 gain gain NOUN cana-844 71 30 is be AUX cana-844 71 31 a a DET cana-844 71 32 measure measure NOUN cana-844 71 33 used use VERB cana-844 71 34 in in ADP cana-844 71 35 decision decision NOUN cana-844 71 36 trees tree NOUN cana-844 71 37 to to PART cana-844 71 38 choose choose VERB cana-844 71 39 the the DET cana-844 71 40 attribute attribute NOUN cana-844 71 41 that that PRON cana-844 71 42 best good ADJ cana-844 71 43 separates separate VERB cana-844 71 44 the the DET cana-844 71 45 classes class NOUN cana-844 71 46 . . PUNCT cana-844 72 1 it it PRON cana-844 72 2 is be AUX cana-844 72 3 calculated calculate VERB cana-844 72 4 as as ADP cana-844 72 5 the the DET cana-844 72 6 difference difference NOUN cana-844 72 7 between between ADP cana-844 72 8 the the DET cana-844 72 9 entropy entropy NOUN cana-844 72 10 of of ADP cana-844 72 11 the the DET cana-844 72 12 parent parent NOUN cana-844 72 13 set set VERB cana-844 72 14 h(t h(t PROPN cana-844 72 15 ) ) PUNCT cana-844 72 16 and and CCONJ cana-844 72 17 the the DET cana-844 72 18 weighted weighted ADJ cana-844 72 19 sum sum NOUN cana-844 72 20 of of ADP cana-844 72 21 the the DET cana-844 72 22 entropies entropy NOUN cana-844 72 23 of of ADP cana-844 72 24 each each DET cana-844 72 25 subset subset VERB cana-844 72 26 h(tv).this h(tv).this PRON cana-844 72 27 measure measure NOUN cana-844 72 28 helps help VERB cana-844 72 29 in in ADP cana-844 72 30 maximizing maximize VERB cana-844 72 31 the the DET cana-844 72 32 effectiveness effectiveness NOUN cana-844 72 33 of of ADP cana-844 72 34 each each DET cana-844 72 35 split split NOUN cana-844 72 36 in in ADP cana-844 72 37 the the DET cana-844 72 38 tree tree NOUN cana-844 72 39 , , PUNCT cana-844 72 40 which which PRON cana-844 72 41 is be AUX cana-844 72 42 crucial crucial ADJ cana-844 72 43 for for ADP cana-844 72 44 handling handle VERB cana-844 72 45 complex complex ADJ cana-844 72 46 feature feature NOUN cana-844 72 47 interactions interaction NOUN cana-844 72 48 in in ADP cana-844 72 49 radiogenomic radiogenomic ADJ cana-844 72 50 data datum NOUN cana-844 72 51 . . PUNCT cana-844 73 1 mean mean VERB cana-844 73 2 squared square VERB cana-844 73 3 error error NOUN cana-844 73 4 ( ( PUNCT cana-844 73 5 mse mse NOUN cana-844 73 6 ): ): PUNCT cana-844 73 7 communications communication NOUN cana-844 73 8 on on ADP cana-844 73 9 applied apply VERB cana-844 73 10 nonlinear nonlinear ADJ cana-844 73 11 analysis analysis NOUN cana-844 73 12 issn issn NOUN cana-844 73 13 : : PUNCT cana-844 73 14 1074 1074 NUM cana-844 73 15 - - PUNCT cana-844 73 16 133x 133x NUM cana-844 73 17 vol vol NOUN cana-844 73 18 31 31 NUM cana-844 73 19 no no NOUN cana-844 73 20 . . PUNCT cana-844 74 1 4s 4s NUM cana-844 74 2 ( ( PUNCT cana-844 74 3 2024 2024 NUM cana-844 74 4 ) ) PUNCT cana-844 74 5 233 233 NUM cana-844 74 6 https://internationalpubls.com https://internationalpubls.com X cana-844 74 7 𝑀𝑆𝐸 𝑀𝑆𝐸 ADP cana-844 74 8 βˆ’ βˆ’ PROPN cana-844 74 9 1 1 NUM cana-844 74 10 𝑛 𝑛 PROPN cana-844 74 11 βˆ‘ βˆ‘ ADP cana-844 74 12 β€Š β€Š SPACE cana-844 74 13 𝑛 𝑛 PRON cana-844 74 14 π‘–βˆ’1 π‘–βˆ’1 PROPN cana-844 74 15 ( ( PUNCT cana-844 74 16 οΏ½ οΏ½ PROPN cana-844 74 17 Μ‚ Μ‚ VERB cana-844 74 18 οΏ½ οΏ½ NOUN cana-844 74 19 𝑖 𝑖 SYM cana-844 74 20 βˆ’ βˆ’ PROPN cana-844 74 21 𝑦𝑖 𝑦𝑖 PROPN cana-844 74 22 ) ) PUNCT cana-844 74 23 2 2 NUM cana-844 74 24 ( ( PUNCT cana-844 74 25 14 14 NUM cana-844 74 26 ) ) PUNCT cana-844 74 27 mse mse NOUN cana-844 74 28 is be AUX cana-844 74 29 a a DET cana-844 74 30 common common ADJ cana-844 74 31 loss loss NOUN cana-844 74 32 function function NOUN cana-844 74 33 used use VERB cana-844 74 34 in in ADP cana-844 74 35 regression regression NOUN cana-844 74 36 problems problem NOUN cana-844 74 37 and and CCONJ cana-844 74 38 measures measure NOUN cana-844 74 39 the the DET cana-844 74 40 average average NOUN cana-844 74 41 of of ADP cana-844 74 42 the the DET cana-844 74 43 squares square NOUN cana-844 74 44 of of ADP cana-844 74 45 the the DET cana-844 74 46 errors error NOUN cana-844 74 47 β€” β€” PUNCT cana-844 74 48 that that ADV cana-844 74 49 is is ADV cana-844 74 50 , , PUNCT cana-844 74 51 the the DET cana-844 74 52 average average ADJ cana-844 74 53 squared square VERB cana-844 74 54 difference difference NOUN cana-844 74 55 between between ADP cana-844 74 56 the the DET cana-844 74 57 estimated estimate VERB cana-844 74 58 values value NOUN cana-844 74 59 and and CCONJ cana-844 74 60 the the DET cana-844 74 61 actual actual ADJ cana-844 74 62 value value NOUN cana-844 74 63 ( ( PUNCT cana-844 74 64 yi yi NOUN cana-844 74 65 ) ) PUNCT cana-844 74 66 . . PUNCT cana-844 75 1 in in ADP cana-844 75 2 the the DET cana-844 75 3 context context NOUN cana-844 75 4 of of ADP cana-844 75 5 radiogenomics radiogenomic NOUN cana-844 75 6 , , PUNCT cana-844 75 7 although although SCONJ cana-844 75 8 primarily primarily ADV cana-844 75 9 a a DET cana-844 75 10 classification classification NOUN cana-844 75 11 setting setting NOUN cana-844 75 12 , , PUNCT cana-844 75 13 regression regression NOUN cana-844 75 14 frameworks framework NOUN cana-844 75 15 might might AUX cana-844 75 16 be be AUX cana-844 75 17 employed employ VERB cana-844 75 18 in in ADP cana-844 75 19 scenarios scenario NOUN cana-844 75 20 involving involve VERB cana-844 75 21 quantitative quantitative ADJ cana-844 75 22 trait trait NOUN cana-844 75 23 predictions prediction NOUN cana-844 75 24 . . PUNCT cana-844 76 1 regularization regularization NOUN cana-844 76 2 ( ( PUNCT cana-844 76 3 l2 l2 NOUN cana-844 76 4 norm norm NOUN cana-844 76 5 ): ): PUNCT cana-844 76 6 Ο‰(πœƒ)βˆ’βˆ₯ Ο‰(πœƒ)βˆ’βˆ₯ PROPN cana-844 76 7 πœƒ πœƒ PRON cana-844 76 8 βˆ₯2 βˆ₯2 ADV cana-844 76 9 ( ( PUNCT cana-844 76 10 15 15 NUM cana-844 76 11 ) ) PUNCT cana-844 76 12 l2 l2 NOUN cana-844 76 13 regularization regularization NOUN cana-844 76 14 adds add VERB cana-844 76 15 a a DET cana-844 76 16 penalty penalty NOUN cana-844 76 17 equivalent equivalent ADJ cana-844 76 18 to to ADP cana-844 76 19 the the DET cana-844 76 20 square square NOUN cana-844 76 21 of of ADP cana-844 76 22 the the DET cana-844 76 23 magnitude magnitude NOUN cana-844 76 24 of of ADP cana-844 76 25 coefficients coefficient NOUN cana-844 76 26 to to ADP cana-844 76 27 the the DET cana-844 76 28 loss loss NOUN cana-844 76 29 function function NOUN cana-844 76 30 . . PUNCT cana-844 77 1 this this PRON cana-844 77 2 discourages discourage VERB cana-844 77 3 large large ADJ cana-844 77 4 weights weight NOUN cana-844 77 5 in in ADP cana-844 77 6 the the DET cana-844 77 7 model model NOUN cana-844 77 8 , , PUNCT cana-844 77 9 leading lead VERB cana-844 77 10 to to ADP cana-844 77 11 simpler simple ADJ cana-844 77 12 models model NOUN cana-844 77 13 that that PRON cana-844 77 14 generalize generalize VERB cana-844 77 15 better well ADV cana-844 77 16 from from ADP cana-844 77 17 training train VERB cana-844 77 18 data datum NOUN cana-844 77 19 to to ADP cana-844 77 20 unseen unseen ADJ cana-844 77 21 data datum NOUN cana-844 77 22 , , PUNCT cana-844 77 23 thus thus ADV cana-844 77 24 preventing prevent VERB cana-844 77 25 overfitting overfitting NOUN cana-844 77 26 β€” β€” PUNCT cana-844 77 27 a a DET cana-844 77 28 significant significant ADJ cana-844 77 29 concern concern NOUN cana-844 77 30 in in ADP cana-844 77 31 highdimensional highdimensional ADJ cana-844 77 32 data datum NOUN cana-844 77 33 settings setting NOUN cana-844 77 34 like like ADP cana-844 77 35 radio radio NOUN cana-844 77 36 genomics genomic NOUN cana-844 77 37 . . PUNCT cana-844 78 1 principal principal ADJ cana-844 78 2 component component NOUN cana-844 78 3 analysis analysis NOUN cana-844 78 4 ( ( PUNCT cana-844 78 5 pca pca NOUN cana-844 78 6 ) ) PUNCT cana-844 78 7 transformation transformation NOUN cana-844 78 8 : : PUNCT cana-844 78 9 π‘Œ π‘Œ PROPN cana-844 78 10 βˆ’ βˆ’ PROPN cana-844 78 11 π‘‹π‘Š π‘‹π‘Š NOUN cana-844 78 12 ( ( PUNCT cana-844 78 13 16 16 NUM cana-844 78 14 ) ) PUNCT cana-844 78 15 pca pca NOUN cana-844 78 16 is be AUX cana-844 78 17 used use VERB cana-844 78 18 for for ADP cana-844 78 19 dimensionality dimensionality NOUN cana-844 78 20 reduction reduction NOUN cana-844 78 21 by by ADP cana-844 78 22 transforming transform VERB cana-844 78 23 the the DET cana-844 78 24 original original ADJ cana-844 78 25 variables variable NOUN cana-844 78 26 into into ADP cana-844 78 27 a a DET cana-844 78 28 new new ADJ cana-844 78 29 set set NOUN cana-844 78 30 of of ADP cana-844 78 31 variables variable NOUN cana-844 78 32 ( ( PUNCT cana-844 78 33 principal principal ADJ cana-844 78 34 components component NOUN cana-844 78 35 ) ) PUNCT cana-844 78 36 , , PUNCT cana-844 78 37 which which PRON cana-844 78 38 are be AUX cana-844 78 39 uncorrelated uncorrelate VERB cana-844 78 40 and and CCONJ cana-844 78 41 ordered order VERB cana-844 78 42 so so SCONJ cana-844 78 43 that that SCONJ cana-844 78 44 the the DET cana-844 78 45 first first ADJ cana-844 78 46 few few ADJ cana-844 78 47 retain retain VERB cana-844 78 48 most most ADJ cana-844 78 49 of of ADP cana-844 78 50 the the DET cana-844 78 51 variation variation NOUN cana-844 78 52 present present ADJ cana-844 78 53 in in ADP cana-844 78 54 all all PRON cana-844 78 55 of of ADP cana-844 78 56 the the DET cana-844 78 57 original original ADJ cana-844 78 58 variables variable NOUN cana-844 78 59 . . PUNCT cana-844 79 1 this this DET cana-844 79 2 transformation transformation NOUN cana-844 79 3 y y PROPN cana-844 79 4 of of ADP cana-844 79 5 the the DET cana-844 79 6 data datum NOUN cana-844 79 7 matrix matrix NOUN cana-844 79 8 x x ADP cana-844 79 9 using use VERB cana-844 79 10 the the DET cana-844 79 11 weight weight NOUN cana-844 79 12 matrix matrix NOUN cana-844 79 13 w w NOUN cana-844 79 14 is be AUX cana-844 79 15 crucial crucial ADJ cana-844 79 16 for for ADP cana-844 79 17 reducing reduce VERB cana-844 79 18 the the DET cana-844 79 19 computational computational ADJ cana-844 79 20 complexity complexity NOUN cana-844 79 21 and and CCONJ cana-844 79 22 enhancing enhance VERB cana-844 79 23 the the DET cana-844 79 24 interpretability interpretability NOUN cana-844 79 25 of of ADP cana-844 79 26 radiogenomic radiogenomic ADJ cana-844 79 27 data datum NOUN cana-844 79 28 analysis analysis NOUN cana-844 79 29 feature feature NOUN cana-844 79 30 scaling scaling NOUN cana-844 79 31 ( ( PUNCT cana-844 79 32 standardization standardization NOUN cana-844 79 33 ): ): PUNCT cana-844 79 34 𝑧 𝑧 PROPN cana-844 79 35 βˆ’ βˆ’ PROPN cana-844 79 36 ( ( PUNCT cana-844 79 37 π‘₯βˆ’πœ‡ π‘₯βˆ’πœ‡ PROPN cana-844 79 38 ) ) PUNCT cana-844 79 39 𝜎 𝜎 PROPN cana-844 79 40 ( ( PUNCT cana-844 79 41 17 17 NUM cana-844 79 42 ) ) PUNCT cana-844 79 43 standardization standardization NOUN cana-844 79 44 involves involve VERB cana-844 79 45 rescaling rescale VERB cana-844 79 46 the the DET cana-844 79 47 features feature NOUN cana-844 79 48 so so SCONJ cana-844 79 49 that that SCONJ cana-844 79 50 they they PRON cana-844 79 51 have have VERB cana-844 79 52 the the DET cana-844 79 53 properties property NOUN cana-844 79 54 of of ADP cana-844 79 55 a a DET cana-844 79 56 standard standard ADJ cana-844 79 57 normal normal ADJ cana-844 79 58 distribution distribution NOUN cana-844 79 59 . . PUNCT cana-844 80 1 this this PRON cana-844 80 2 is be AUX cana-844 80 3 crucial crucial ADJ cana-844 80 4 in in ADP cana-844 80 5 data datum NOUN cana-844 80 6 preprocessing preprocesse VERB cana-844 80 7 for for ADP cana-844 80 8 machine machine NOUN cana-844 80 9 learning learn VERB cana-844 80 10 algorithms algorithm NOUN cana-844 80 11 to to PART cana-844 80 12 perform perform VERB cana-844 80 13 optimally optimally ADV cana-844 80 14 , , PUNCT cana-844 80 15 particularly particularly ADV cana-844 80 16 in in ADP cana-844 80 17 radiogenomics radiogenomic NOUN cana-844 80 18 where where SCONJ cana-844 80 19 features feature NOUN cana-844 80 20 might might AUX cana-844 80 21 have have VERB cana-844 80 22 different different ADJ cana-844 80 23 units unit NOUN cana-844 80 24 and and CCONJ cana-844 80 25 scales scale VERB cana-844 80 26 adaboost adaboost ADJ cana-844 80 27 algorithm algorithm NOUN cana-844 80 28 update update NOUN cana-844 80 29 weights weight NOUN cana-844 80 30 : : PUNCT cana-844 80 31 𝑀(𝑖 𝑀(𝑖 NOUN cana-844 80 32 ) ) PUNCT cana-844 80 33 ← ← PROPN cana-844 80 34 𝑀(𝑖 𝑀(𝑖 NOUN cana-844 80 35 ) ) PUNCT cana-844 80 36 β‹… β‹… PROPN cana-844 80 37 π‘’βˆ’π›Όπ‘¦ π‘’βˆ’π›Όπ‘¦ NOUN cana-844 80 38 ( ( PUNCT cana-844 80 39 1)𝑓(𝑧(1 1)𝑓(𝑧(1 NUM cana-844 80 40 ) ) PUNCT cana-844 80 41 ) ) PUNCT cana-844 80 42 ( ( PUNCT cana-844 80 43 18 18 NUM cana-844 80 44 ) ) PUNCT cana-844 80 45 adaboost adaboost ADV cana-844 80 46 is be AUX cana-844 80 47 an an DET cana-844 80 48 ensemble ensemble ADJ cana-844 80 49 technique technique NOUN cana-844 80 50 that that PRON cana-844 80 51 combines combine VERB cana-844 80 52 multiple multiple ADJ cana-844 80 53 weak weak ADJ cana-844 80 54 classifiers classifier NOUN cana-844 80 55 to to PART cana-844 80 56 form form VERB cana-844 80 57 a a DET cana-844 80 58 strong strong ADJ cana-844 80 59 classifier classifier NOUN cana-844 80 60 . . PUNCT cana-844 81 1 after after SCONJ cana-844 81 2 each each DET cana-844 81 3 classifier classifier NOUN cana-844 81 4 is be AUX cana-844 81 5 trained train VERB cana-844 81 6 , , PUNCT cana-844 81 7 the the DET cana-844 81 8 weights weight NOUN cana-844 81 9 of of ADP cana-844 81 10 incorrectly incorrectly ADV cana-844 81 11 classified classified ADJ cana-844 81 12 instances instance NOUN cana-844 81 13 are be AUX cana-844 81 14 increased increase VERB cana-844 81 15 so so SCONJ cana-844 81 16 that that SCONJ cana-844 81 17 subsequent subsequent ADJ cana-844 81 18 classifiers classifier NOUN cana-844 81 19 focus focus VERB cana-844 81 20 more more ADV cana-844 81 21 on on ADP cana-844 81 22 difficult difficult ADJ cana-844 81 23 cases case NOUN cana-844 81 24 . . PUNCT cana-844 82 1 this this DET cana-844 82 2 method method NOUN cana-844 82 3 is be AUX cana-844 82 4 beneficial beneficial ADJ cana-844 82 5 in in ADP cana-844 82 6 radiogenomics radiogenomic NOUN cana-844 82 7 , , PUNCT cana-844 82 8 where where SCONJ cana-844 82 9 the the DET cana-844 82 10 integration integration NOUN cana-844 82 11 of of ADP cana-844 82 12 diverse diverse ADJ cana-844 82 13 data datum NOUN cana-844 82 14 types type NOUN cana-844 82 15 and and CCONJ cana-844 82 16 complex complex ADJ cana-844 82 17 patterns pattern NOUN cana-844 82 18 makes make VERB cana-844 82 19 robust robust ADJ cana-844 82 20 classification classification NOUN cana-844 82 21 challenging challenging ADJ cana-844 82 22 . . PUNCT cana-844 83 1 deep deep ADJ cana-844 83 2 learning learn VERB cana-844 83 3 weight weight NOUN cana-844 83 4 initialization initialization NOUN cana-844 83 5 ( ( PUNCT cana-844 83 6 he he PRON cana-844 83 7 initialization initialization NOUN cana-844 83 8 ): ): PUNCT cana-844 83 9 π‘Š π‘Š NOUN cana-844 83 10 ∼ ∼ NOUN cana-844 83 11 𝒩(0,√ 𝒩(0,√ PROPN cana-844 83 12 2 2 NUM cana-844 83 13 ear_in ear_in NOUN cana-844 83 14 ) ) PUNCT cana-844 83 15 ( ( PUNCT cana-844 83 16 19 19 NUM cana-844 83 17 ) ) PUNCT cana-844 83 18 proper proper ADJ cana-844 83 19 initialization initialization NOUN cana-844 83 20 of of ADP cana-844 83 21 neural neural ADJ cana-844 83 22 network network NOUN cana-844 83 23 weights weight NOUN cana-844 83 24 is be AUX cana-844 83 25 critical critical ADJ cana-844 83 26 for for ADP cana-844 83 27 ensuring ensure VERB cana-844 83 28 that that SCONJ cana-844 83 29 the the DET cana-844 83 30 network network NOUN cana-844 83 31 converges converge VERB cana-844 83 32 quickly quickly ADV cana-844 83 33 and and CCONJ cana-844 83 34 reliably reliably ADV cana-844 83 35 to to ADP cana-844 83 36 a a DET cana-844 83 37 good good ADJ cana-844 83 38 solution solution NOUN cana-844 83 39 . . PUNCT cana-844 84 1 he he PRON cana-844 84 2 initialization initialization NOUN cana-844 84 3 specifically specifically ADV cana-844 84 4 helps help VERB cana-844 84 5 in in ADP cana-844 84 6 maintaining maintain VERB cana-844 84 7 the the DET cana-844 84 8 variance variance NOUN cana-844 84 9 communications communication NOUN cana-844 84 10 on on ADP cana-844 84 11 applied apply VERB cana-844 84 12 nonlinear nonlinear ADJ cana-844 84 13 analysis analysis NOUN cana-844 84 14 issn issn NOUN cana-844 84 15 : : PUNCT cana-844 84 16 1074 1074 NUM cana-844 84 17 - - PUNCT cana-844 84 18 133x 133x NUM cana-844 84 19 vol vol NOUN cana-844 84 20 31 31 NUM cana-844 84 21 no no NOUN cana-844 84 22 . . PUNCT cana-844 85 1 4s 4s NUM cana-844 85 2 ( ( PUNCT cana-844 85 3 2024 2024 NUM cana-844 85 4 ) ) PUNCT cana-844 85 5 234 234 NUM cana-844 85 6 https://internationalpubls.com https://internationalpubls.com X cana-844 85 7 of of ADP cana-844 85 8 activations activation NOUN cana-844 85 9 across across ADP cana-844 85 10 layers layer NOUN cana-844 85 11 , , PUNCT cana-844 85 12 which which PRON cana-844 85 13 is be AUX cana-844 85 14 crucial crucial ADJ cana-844 85 15 when when SCONJ cana-844 85 16 training train VERB cana-844 85 17 deep deep ADJ cana-844 85 18 networks network NOUN cana-844 85 19 with with ADP cana-844 85 20 relu relu NOUN cana-844 85 21 activations activation NOUN cana-844 85 22 , , PUNCT cana-844 85 23 commonly commonly ADV cana-844 85 24 used use VERB cana-844 85 25 in in ADP cana-844 85 26 analyzing analyze VERB cana-844 85 27 medical medical ADJ cana-844 85 28 images image NOUN cana-844 85 29 . . PUNCT cana-844 86 1 in in ADP cana-844 86 2 conclusion conclusion NOUN cana-844 86 3 , , PUNCT cana-844 86 4 our our PRON cana-844 86 5 all all ADV cana-844 86 6 - - PUNCT cana-844 86 7 encompassing encompass VERB cana-844 86 8 strategy strategy NOUN cana-844 86 9 that that PRON cana-844 86 10 makes make VERB cana-844 86 11 use use NOUN cana-844 86 12 of of ADP cana-844 86 13 cutting cut VERB cana-844 86 14 - - PUNCT cana-844 86 15 edge edge NOUN cana-844 86 16 machine machine NOUN cana-844 86 17 learning learning NOUN cana-844 86 18 and and CCONJ cana-844 86 19 deep deep ADJ cana-844 86 20 learning learning NOUN cana-844 86 21 methodologies methodology NOUN cana-844 86 22 , , PUNCT cana-844 86 23 as as ADV cana-844 86 24 well well ADV cana-844 86 25 as as ADP cana-844 86 26 meticulous meticulous ADJ cana-844 86 27 feature feature NOUN cana-844 86 28 selection selection NOUN cana-844 86 29 and and CCONJ cana-844 86 30 data datum NOUN cana-844 86 31 integration integration NOUN cana-844 86 32 procedures procedure NOUN cana-844 86 33 , , PUNCT cana-844 86 34 promises promise NOUN cana-844 86 35 to to PART cana-844 86 36 yield yield VERB cana-844 86 37 precise precise ADJ cana-844 86 38 estimations estimation NOUN cana-844 86 39 of of ADP cana-844 86 40 the the DET cana-844 86 41 mgmt mgmt PROPN cana-844 86 42 promoter promoter NOUN cana-844 86 43 methylation methylation NOUN cana-844 86 44 status status NOUN cana-844 86 45 in in ADP cana-844 86 46 gliomas glioma NOUN cana-844 86 47 . . PUNCT cana-844 87 1 this this PRON cana-844 87 2 will will AUX cana-844 87 3 provide provide VERB cana-844 87 4 insightful insightful ADJ cana-844 87 5 information information NOUN cana-844 87 6 for for ADP cana-844 87 7 customised customised ADJ cana-844 87 8 treatment treatment NOUN cana-844 87 9 plans plan NOUN cana-844 87 10 and and CCONJ cana-844 87 11 enhanced enhance VERB cana-844 87 12 outcomes outcome NOUN cana-844 87 13 for for ADP cana-844 87 14 patients patient NOUN cana-844 87 15 in in ADP cana-844 87 16 the the DET cana-844 87 17 field field NOUN cana-844 87 18 of of ADP cana-844 87 19 neuro neuro NOUN cana-844 87 20 - - PUNCT cana-844 87 21 oncology oncology NOUN cana-844 87 22 . . PUNCT cana-844 88 1 2 2 X cana-844 88 2 . . X cana-844 88 3 literature literature NOUN cana-844 88 4 review review NOUN cana-844 88 5 in in ADP cana-844 88 6 this this DET cana-844 88 7 work work NOUN cana-844 88 8 , , PUNCT cana-844 88 9 glioblastoma glioblastoma NOUN cana-844 88 10 patients patient NOUN cana-844 88 11 ' ' PART cana-844 88 12 preoperative preoperative ADJ cana-844 88 13 brain brain NOUN cana-844 88 14 mris mris PROPN cana-844 88 15 are be AUX cana-844 88 16 used use VERB cana-844 88 17 to to PART cana-844 88 18 identify identify VERB cana-844 88 19 genetic genetic ADJ cana-844 88 20 indicators indicator NOUN cana-844 88 21 using use VERB cana-844 88 22 artificial artificial ADJ cana-844 88 23 intelligence intelligence NOUN cana-844 88 24 . . PUNCT cana-844 89 1 models model NOUN cana-844 89 2 to to PART cana-844 89 3 predict predict VERB cana-844 89 4 nine nine NUM cana-844 89 5 genetic genetic ADJ cana-844 89 6 indicators indicator NOUN cana-844 89 7 were be AUX cana-844 89 8 constructed construct VERB cana-844 89 9 using use VERB cana-844 89 10 information information NOUN cana-844 89 11 from from ADP cana-844 89 12 400 400 NUM cana-844 89 13 patients patient NOUN cana-844 89 14 . . PUNCT cana-844 90 1 for for ADP cana-844 90 2 a a DET cana-844 90 3 number number NOUN cana-844 90 4 of of ADP cana-844 90 5 biomarkers biomarker NOUN cana-844 90 6 , , PUNCT cana-844 90 7 the the DET cana-844 90 8 combination combination NOUN cana-844 90 9 of of ADP cana-844 90 10 radiomics radiomic NOUN cana-844 90 11 and and CCONJ cana-844 90 12 cnn cnn PROPN cana-844 90 13 features feature NOUN cana-844 90 14 produced produce VERB cana-844 90 15 good good ADJ cana-844 90 16 results result NOUN cana-844 90 17 , , PUNCT cana-844 90 18 with with ADP cana-844 90 19 roc roc PROPN cana-844 90 20 auc auc NOUN cana-844 90 21 > > X cana-844 90 22 0.85 0.85 NUM cana-844 90 23 for for ADP cana-844 90 24 some some PRON cana-844 90 25 and and CCONJ cana-844 90 26 > > X cana-844 90 27 0.7 0.7 NUM cana-844 90 28 for for ADP cana-844 90 29 others other NOUN cana-844 90 30 . . PUNCT cana-844 91 1 for for ADP cana-844 91 2 particular particular ADJ cana-844 91 3 indicators indicator NOUN cana-844 91 4 , , PUNCT cana-844 91 5 combining combine VERB cana-844 91 6 characteristics characteristic NOUN cana-844 91 7 performed perform VERB cana-844 91 8 better well ADV cana-844 91 9 than than ADP cana-844 91 10 separate separate ADJ cana-844 91 11 models model NOUN cana-844 91 12 , , PUNCT cana-844 91 13 suggesting suggest VERB cana-844 91 14 potential potential NOUN cana-844 91 15 for for ADP cana-844 91 16 noninvasive noninvasive ADJ cana-844 91 17 genetic genetic ADJ cana-844 91 18 prediction prediction NOUN cana-844 91 19 in in ADP cana-844 91 20 gliomas glioma NOUN cana-844 91 21 [ [ X cana-844 91 22 5 5 NUM cana-844 91 23 ] ] PUNCT cana-844 91 24 . . PUNCT cana-844 92 1 this this DET cana-844 92 2 work work NOUN cana-844 92 3 investigates investigate VERB cana-844 92 4 the the DET cana-844 92 5 use use NOUN cana-844 92 6 of of ADP cana-844 92 7 mri mri NOUN cana-844 92 8 radiomics radiomic NOUN cana-844 92 9 in in ADP cana-844 92 10 deep deep ADJ cana-844 92 11 learning learning NOUN cana-844 92 12 techniques technique NOUN cana-844 92 13 to to PART cana-844 92 14 predict predict VERB cana-844 92 15 mgmt mgmt PROPN cana-844 92 16 promoter promoter NOUN cana-844 92 17 methylation methylation NOUN cana-844 92 18 in in ADP cana-844 92 19 diffuse diffuse ADJ cana-844 92 20 gliomas glioma NOUN cana-844 92 21 . . PUNCT cana-844 93 1 utilizing utilize VERB cana-844 93 2 information information NOUN cana-844 93 3 from from ADP cana-844 93 4 111 111 NUM cana-844 93 5 patients patient NOUN cana-844 93 6 , , PUNCT cana-844 93 7 radiomic radiomic ADJ cana-844 93 8 characteristics characteristic NOUN cana-844 93 9 were be AUX cana-844 93 10 taken take VERB cana-844 93 11 from from ADP cana-844 93 12 four four NUM cana-844 93 13 different different ADJ cana-844 93 14 mri mri NOUN cana-844 93 15 sequences sequence NOUN cana-844 93 16 ' ' PART cana-844 93 17 discrete discrete ADJ cana-844 93 18 regions region NOUN cana-844 93 19 of of ADP cana-844 93 20 interest interest NOUN cana-844 93 21 and and CCONJ cana-844 93 22 supplied supply VERB cana-844 93 23 into into ADP cana-844 93 24 a a DET cana-844 93 25 residual residual ADJ cana-844 93 26 network network NOUN cana-844 93 27 model model NOUN cana-844 93 28 . . PUNCT cana-844 94 1 models model NOUN cana-844 94 2 were be AUX cana-844 94 3 trained train VERB cana-844 94 4 and and CCONJ cana-844 94 5 evaluated evaluate VERB cana-844 94 6 using use VERB cana-844 94 7 five five NUM cana-844 94 8 - - ADJ cana-844 94 9 fold fold ADJ cana-844 94 10 cross cross NOUN cana-844 94 11 - - NOUN cana-844 94 12 validation validation ADJ cana-844 94 13 ; ; PUNCT cana-844 94 14 area area NOUN cana-844 94 15 under under ADP cana-844 94 16 the the DET cana-844 94 17 curve curve NOUN cana-844 94 18 and and CCONJ cana-844 94 19 average average ADJ cana-844 94 20 accuracy accuracy NOUN cana-844 94 21 metrics metric NOUN cana-844 94 22 were be AUX cana-844 94 23 used use VERB cana-844 94 24 to to PART cana-844 94 25 evaluate evaluate VERB cana-844 94 26 performance performance NOUN cana-844 94 27 . . PUNCT cana-844 95 1 with with ADP cana-844 95 2 an an DET cana-844 95 3 auc auc NOUN cana-844 95 4 of of ADP cana-844 95 5 0.90 0.90 NUM cana-844 95 6 and and CCONJ cana-844 95 7 an an DET cana-844 95 8 average average ADJ cana-844 95 9 accuracy accuracy NOUN cana-844 95 10 of of ADP cana-844 95 11 0.91 0.91 NUM cana-844 95 12 , , PUNCT cana-844 95 13 the the DET cana-844 95 14 best well ADV cana-844 95 15 - - PUNCT cana-844 95 16 performing perform VERB cana-844 95 17 model model NOUN cana-844 95 18 , , PUNCT cana-844 95 19 which which PRON cana-844 95 20 was be AUX cana-844 95 21 based base VERB cana-844 95 22 on on ADP cana-844 95 23 the the DET cana-844 95 24 roi roi NOUN cana-844 95 25 of of ADP cana-844 95 26 the the DET cana-844 95 27 tumor tumor NOUN cana-844 95 28 core core NOUN cana-844 95 29 and and CCONJ cana-844 95 30 included include VERB cana-844 95 31 t1 t1 NOUN cana-844 95 32 contrast contrast NOUN cana-844 95 33 - - PUNCT cana-844 95 34 enhanced enhance VERB cana-844 95 35 and and CCONJ cana-844 95 36 apparent apparent ADJ cana-844 95 37 diffusion diffusion NOUN cana-844 95 38 coefficient coefficient NOUN cana-844 95 39 data data PROPN cana-844 95 40 , , PUNCT cana-844 95 41 showed show VERB cana-844 95 42 superior superior ADJ cana-844 95 43 diagnostic diagnostic ADJ cana-844 95 44 accuracy accuracy NOUN cana-844 96 1 [ [ X cana-844 96 2 6 6 NUM cana-844 96 3 ] ] PUNCT cana-844 96 4 . . PUNCT cana-844 97 1 in in ADP cana-844 97 2 this this DET cana-844 97 3 work work NOUN cana-844 97 4 , , PUNCT cana-844 97 5 the the DET cana-844 97 6 authors author NOUN cana-844 97 7 evaluated evaluate VERB cana-844 97 8 the the DET cana-844 97 9 viability viability NOUN cana-844 97 10 of of ADP cana-844 97 11 using use VERB cana-844 97 12 mri mri NOUN cana-844 97 13 to to PART cana-844 97 14 predict predict VERB cana-844 97 15 mgmt mgmt PROPN cana-844 97 16 methylation methylation NOUN cana-844 97 17 in in ADP cana-844 97 18 gliomas glioma NOUN cana-844 97 19 by by ADP cana-844 97 20 extensively extensively ADV cana-844 97 21 testing test VERB cana-844 97 22 a a DET cana-844 97 23 number number NOUN cana-844 97 24 of of ADP cana-844 97 25 new new ADJ cana-844 97 26 cnn cnn PROPN cana-844 97 27 designs design NOUN cana-844 97 28 . . PUNCT cana-844 98 1 the the DET cana-844 98 2 thorough thorough ADJ cana-844 98 3 trials trial NOUN cana-844 98 4 showed show VERB cana-844 98 5 that that SCONJ cana-844 98 6 , , PUNCT cana-844 98 7 in in ADP cana-844 98 8 terms term NOUN cana-844 98 9 of of ADP cana-844 98 10 external external ADJ cana-844 98 11 validation validation NOUN cana-844 98 12 accuracy accuracy NOUN cana-844 98 13 , , PUNCT cana-844 98 14 almost almost ADV cana-844 98 15 80 80 NUM cana-844 98 16 % % NOUN cana-844 98 17 of of ADP cana-844 98 18 the the DET cana-844 98 19 constructed construct VERB cana-844 98 20 models model NOUN cana-844 98 21 did do AUX cana-844 98 22 not not PART cana-844 98 23 significantly significantly ADV cana-844 98 24 outperform outperform VERB cana-844 98 25 chance chance NOUN cana-844 98 26 levels level NOUN cana-844 98 27 . . PUNCT cana-844 99 1 the the DET cana-844 99 2 rsna rsna NOUN cana-844 99 3 - - PUNCT cana-844 99 4 miccai miccai NOUN cana-844 99 5 challenge challenge NOUN cana-844 99 6 's 's PART cana-844 99 7 top top ADJ cana-844 99 8 solution solution NOUN cana-844 99 9 performed perform VERB cana-844 99 10 only only ADV cana-844 99 11 moderately moderately ADV cana-844 99 12 well well ADV cana-844 99 13 , , PUNCT cana-844 99 14 even even ADV cana-844 99 15 after after ADP cana-844 99 16 external external ADJ cana-844 99 17 validation validation NOUN cana-844 99 18 . . PUNCT cana-844 100 1 these these DET cana-844 100 2 results result NOUN cana-844 100 3 imply imply VERB cana-844 100 4 that that SCONJ cana-844 100 5 , , PUNCT cana-844 100 6 even even ADV cana-844 100 7 with with ADP cana-844 100 8 deep deep ADJ cana-844 100 9 learning learning NOUN cana-844 100 10 techniques technique NOUN cana-844 100 11 , , PUNCT cana-844 100 12 predicting predict VERB cana-844 100 13 the the DET cana-844 100 14 mgmt mgmt PROPN cana-844 100 15 methylation methylation PROPN cana-844 100 16 status status NOUN cana-844 100 17 in in ADP cana-844 100 18 gliomas glioma NOUN cana-844 100 19 using use VERB cana-844 100 20 preoperative preoperative ADJ cana-844 100 21 mri mri NOUN cana-844 100 22 may may AUX cana-844 100 23 prove prove VERB cana-844 100 24 difficult difficult ADJ cana-844 100 25 , , PUNCT cana-844 100 26 despite despite SCONJ cana-844 100 27 initial initial ADJ cana-844 100 28 promise promise NOUN cana-844 100 29 [ [ X cana-844 100 30 7 7 NUM cana-844 100 31 ] ] PUNCT cana-844 100 32 . . PUNCT cana-844 101 1 an an DET cana-844 101 2 attention attention NOUN cana-844 101 3 - - PUNCT cana-844 101 4 based base VERB cana-844 101 5 deep deep ADJ cana-844 101 6 learning learning NOUN cana-844 101 7 network network NOUN cana-844 101 8 for for ADP cana-844 101 9 mgmt mgmt PROPN cana-844 101 10 methylation methylation PROPN cana-844 101 11 status status NOUN cana-844 101 12 prediction prediction NOUN cana-844 101 13 in in ADP cana-844 101 14 gbm gbm PROPN cana-844 101 15 is be AUX cana-844 101 16 presented present VERB cana-844 101 17 in in ADP cana-844 101 18 this this DET cana-844 101 19 paper paper NOUN cana-844 101 20 . . PUNCT cana-844 102 1 existing exist VERB cana-844 102 2 techniques technique NOUN cana-844 102 3 , , PUNCT cana-844 102 4 which which PRON cana-844 102 5 rely rely VERB cana-844 102 6 on on ADP cana-844 102 7 radiomic radiomic ADJ cana-844 102 8 studies study NOUN cana-844 102 9 , , PUNCT cana-844 102 10 might might AUX cana-844 102 11 be be AUX cana-844 102 12 deficient deficient ADJ cana-844 102 13 in in ADP cana-844 102 14 crucial crucial ADJ cana-844 102 15 elements element NOUN cana-844 102 16 needed need VERB cana-844 102 17 for for ADP cana-844 102 18 precise precise ADJ cana-844 102 19 prediction prediction NOUN cana-844 102 20 . . PUNCT cana-844 103 1 although although SCONJ cana-844 103 2 deep deep ADJ cana-844 103 3 learning learning NOUN cana-844 103 4 techniques technique NOUN cana-844 103 5 have have AUX cana-844 103 6 become become VERB cana-844 103 7 popular popular ADJ cana-844 103 8 , , PUNCT cana-844 103 9 they they PRON cana-844 103 10 frequently frequently ADV cana-844 103 11 necessitate necessitate VERB cana-844 103 12 a a DET cana-844 103 13 thorough thorough ADJ cana-844 103 14 analysis analysis NOUN cana-844 103 15 of of ADP cana-844 103 16 the the DET cana-844 103 17 data datum NOUN cana-844 103 18 . . PUNCT cana-844 104 1 the the DET cana-844 104 2 authors author NOUN cana-844 104 3 suggested suggest VERB cana-844 104 4 a a DET cana-844 104 5 squeezeand squeezeand NOUN cana-844 104 6 - - PUNCT cana-844 104 7 sequence sequence NOUN cana-844 104 8 attention attention NOUN cana-844 104 9 mechanism mechanism NOUN cana-844 104 10 to to PART cana-844 104 11 rank rank VERB cana-844 104 12 pertinent pertinent ADJ cana-844 104 13 slices slice NOUN cana-844 104 14 and and CCONJ cana-844 104 15 areas area NOUN cana-844 104 16 in in ADP cana-844 104 17 order order NOUN cana-844 104 18 to to PART cana-844 104 19 remedy remedy VERB cana-844 104 20 this this PRON cana-844 104 21 . . PUNCT cana-844 105 1 the the DET cana-844 105 2 best good ADJ cana-844 105 3 auc auc NOUN cana-844 105 4 of of ADP cana-844 105 5 70.59 70.59 NUM cana-844 105 6 was be AUX cana-844 105 7 obtained obtain VERB cana-844 105 8 after after ADP cana-844 105 9 evaluation evaluation NOUN cana-844 105 10 using use VERB cana-844 105 11 different different ADJ cana-844 105 12 binary binary ADJ cana-844 105 13 classification classification NOUN cana-844 105 14 measures measure NOUN cana-844 105 15 [ [ X cana-844 105 16 8 8 NUM cana-844 105 17 ] ] PUNCT cana-844 105 18 . . PUNCT cana-844 106 1 this this DET cana-844 106 2 study study NOUN cana-844 106 3 suggests suggest VERB cana-844 106 4 a a DET cana-844 106 5 novel novel ADJ cana-844 106 6 deep deep ADJ cana-844 106 7 - - PUNCT cana-844 106 8 learning learning NOUN cana-844 106 9 - - PUNCT cana-844 106 10 based base VERB cana-844 106 11 classification classification NOUN cana-844 106 12 approach approach NOUN cana-844 106 13 for for ADP cana-844 106 14 glioblastoma glioblastoma NOUN cana-844 106 15 genetic genetic ADJ cana-844 106 16 subtyping subtyping NOUN cana-844 106 17 that that PRON cana-844 106 18 focuses focus VERB cana-844 106 19 on on ADP cana-844 106 20 mgmt mgmt ADJ cana-844 106 21 promoter promoter NOUN cana-844 106 22 methylation methylation NOUN cana-844 106 23 detection detection NOUN cana-844 106 24 in in ADP cana-844 106 25 order order NOUN cana-844 106 26 to to PART cana-844 106 27 speed speed VERB cana-844 106 28 up up ADP cana-844 106 29 tumor tumor NOUN cana-844 106 30 identification identification NOUN cana-844 106 31 and and CCONJ cana-844 106 32 reduce reduce VERB cana-844 106 33 patient patient ADJ cana-844 106 34 anxiety anxiety NOUN cana-844 106 35 . . PUNCT cana-844 107 1 the the DET cana-844 107 2 project project NOUN cana-844 107 3 intends intend VERB cana-844 107 4 to to PART cana-844 107 5 investigate investigate VERB cana-844 107 6 the the DET cana-844 107 7 viability viability NOUN cana-844 107 8 of of ADP cana-844 107 9 employing employ VERB cana-844 107 10 deep deep ADJ cana-844 107 11 learning learning NOUN cana-844 107 12 algorithms algorithm NOUN cana-844 107 13 for for ADP cana-844 107 14 predicting predict VERB cana-844 107 15 mgmt mgmt ADJ cana-844 107 16 promoter promoter NOUN cana-844 107 17 methylation methylation NOUN cana-844 107 18 status status NOUN cana-844 107 19 , , PUNCT cana-844 107 20 presenting present VERB cana-844 107 21 possibilities possibility NOUN cana-844 107 22 for for ADP cana-844 107 23 less less ADV cana-844 107 24 intrusive intrusive ADJ cana-844 107 25 diagnosis diagnosis NOUN cana-844 107 26 and and CCONJ cana-844 107 27 treatment treatment NOUN cana-844 107 28 solutions solution NOUN cana-844 107 29 . . PUNCT cana-844 108 1 it it PRON cana-844 108 2 does do VERB cana-844 108 3 this this PRON cana-844 108 4 by by ADP cana-844 108 5 leveraging leverage VERB cana-844 108 6 the the DET cana-844 108 7 rsna rsna NOUN cana-844 108 8 - - PUNCT cana-844 108 9 miccai miccai NOUN cana-844 108 10 dataset dataset NOUN cana-844 108 11 , , PUNCT cana-844 108 12 which which PRON cana-844 108 13 comprises comprise VERB cana-844 108 14 structural structural ADJ cana-844 108 15 multi multi ADJ cana-844 108 16 - - ADJ cana-844 108 17 parametric parametric ADJ cana-844 108 18 mri mri NOUN cana-844 108 19 scans scan NOUN cana-844 108 20 [ [ X cana-844 108 21 9 9 NUM cana-844 108 22 ] ] PUNCT cana-844 108 23 . . PUNCT cana-844 109 1 communications communication NOUN cana-844 109 2 on on ADP cana-844 109 3 applied apply VERB cana-844 109 4 nonlinear nonlinear ADJ cana-844 109 5 analysis analysis NOUN cana-844 109 6 issn issn NOUN cana-844 109 7 : : PUNCT cana-844 109 8 1074 1074 NUM cana-844 109 9 - - PUNCT cana-844 109 10 133x 133x NUM cana-844 109 11 vol vol NOUN cana-844 109 12 31 31 NUM cana-844 109 13 no no NOUN cana-844 109 14 . . PUNCT cana-844 110 1 4s 4s NUM cana-844 110 2 ( ( PUNCT cana-844 110 3 2024 2024 NUM cana-844 110 4 ) ) PUNCT cana-844 110 5 235 235 NUM cana-844 110 6 https://internationalpubls.com https://internationalpubls.com X cana-844 110 7 in in ADP cana-844 110 8 order order NOUN cana-844 110 9 to to PART cana-844 110 10 improve improve VERB cana-844 110 11 prognosis prognosis NOUN cana-844 110 12 , , PUNCT cana-844 110 13 treatment treatment NOUN cana-844 110 14 response response NOUN cana-844 110 15 , , PUNCT cana-844 110 16 and and CCONJ cana-844 110 17 recurrence recurrence NOUN cana-844 110 18 monitoring monitoring NOUN cana-844 110 19 , , PUNCT cana-844 110 20 this this DET cana-844 110 21 review review NOUN cana-844 110 22 emphasizes emphasize VERB cana-844 110 23 current current ADJ cana-844 110 24 developments development NOUN cana-844 110 25 in in ADP cana-844 110 26 the the DET cana-844 110 27 use use NOUN cana-844 110 28 of of ADP cana-844 110 29 magnetic magnetic ADJ cana-844 110 30 resonance resonance NOUN cana-844 110 31 imaging imaging NOUN cana-844 110 32 ( ( PUNCT cana-844 110 33 mri mri NOUN cana-844 110 34 ) ) PUNCT cana-844 110 35 radiogenomics radiogenomic NOUN cana-844 110 36 to to PART cana-844 110 37 evaluate evaluate VERB cana-844 110 38 genetic genetic ADJ cana-844 110 39 markers marker NOUN cana-844 110 40 in in ADP cana-844 110 41 gbm gbm PROPN cana-844 110 42 . . PUNCT cana-844 111 1 research research NOUN cana-844 111 2 shows show VERB cana-844 111 3 that that SCONJ cana-844 111 4 radiomic radiomic ADJ cana-844 111 5 characteristics characteristic NOUN cana-844 111 6 have have VERB cana-844 111 7 high high ADJ cana-844 111 8 sensitivity sensitivity NOUN cana-844 111 9 and and CCONJ cana-844 111 10 specificity specificity NOUN cana-844 111 11 ; ; PUNCT cana-844 111 12 however however ADV cana-844 111 13 , , PUNCT cana-844 111 14 there there PRON cana-844 111 15 are be VERB cana-844 111 16 still still ADV cana-844 111 17 issues issue NOUN cana-844 111 18 with with ADP cana-844 111 19 accuracy accuracy NOUN cana-844 111 20 , , PUNCT cana-844 111 21 reproducibility reproducibility NOUN cana-844 111 22 , , PUNCT cana-844 111 23 and and CCONJ cana-844 111 24 therapeutic therapeutic ADJ cana-844 111 25 value value NOUN cana-844 111 26 . . PUNCT cana-844 112 1 standardization standardization NOUN cana-844 112 2 and and CCONJ cana-844 112 3 thorough thorough ADJ cana-844 112 4 data datum NOUN cana-844 112 5 analysis analysis NOUN cana-844 112 6 should should AUX cana-844 112 7 be be AUX cana-844 112 8 given give VERB cana-844 112 9 top top ADJ cana-844 112 10 priority priority NOUN cana-844 112 11 in in ADP cana-844 112 12 future future ADJ cana-844 112 13 initiatives initiative NOUN cana-844 112 14 to to PART cana-844 112 15 realize realize VERB cana-844 112 16 the the DET cana-844 112 17 full full ADJ cana-844 112 18 potential potential NOUN cana-844 112 19 of of ADP cana-844 112 20 this this DET cana-844 112 21 intriguing intriguing ADJ cana-844 112 22 strategy strategy NOUN cana-844 112 23 [ [ X cana-844 112 24 10 10 NUM cana-844 112 25 ] ] PUNCT cana-844 112 26 . . PUNCT cana-844 113 1 this this DET cana-844 113 2 work work NOUN cana-844 113 3 investigates investigate VERB cana-844 113 4 three three NUM cana-844 113 5 deep deep ADJ cana-844 113 6 learning learning NOUN cana-844 113 7 - - PUNCT cana-844 113 8 based base VERB cana-844 113 9 methods method NOUN cana-844 113 10 for for ADP cana-844 113 11 utilizing utilize VERB cana-844 113 12 t2wi t2wi PUNCT cana-844 113 13 mri mri NOUN cana-844 113 14 scans scan NOUN cana-844 113 15 to to PART cana-844 113 16 predict predict VERB cana-844 113 17 the the DET cana-844 113 18 methylation methylation NOUN cana-844 113 19 status status NOUN cana-844 113 20 of of ADP cana-844 113 21 the the DET cana-844 113 22 o-6 o-6 PROPN cana-844 113 23 - - PUNCT cana-844 113 24 methylguanine methylguanine NOUN cana-844 113 25 - - PUNCT cana-844 113 26 dna dna NOUN cana-844 113 27 methyltransferase methyltransferase NOUN cana-844 113 28 ( ( PUNCT cana-844 113 29 mgmt mgmt NOUN cana-844 113 30 ) ) PUNCT cana-844 113 31 promoter promoter NOUN cana-844 113 32 in in ADP cana-844 113 33 glioblastoma glioblastoma NOUN cana-844 113 34 . . PUNCT cana-844 114 1 for for ADP cana-844 114 2 individuals individual NOUN cana-844 114 3 with with ADP cana-844 114 4 glioblastoma glioblastoma NOUN cana-844 114 5 , , PUNCT cana-844 114 6 mgmt mgmt NOUN cana-844 114 7 status status NOUN cana-844 114 8 is be AUX cana-844 114 9 a a DET cana-844 114 10 critical critical ADJ cana-844 114 11 prognostic prognostic ADJ cana-844 114 12 factor factor NOUN cana-844 114 13 that that PRON cana-844 114 14 influences influence VERB cana-844 114 15 therapy therapy NOUN cana-844 114 16 choices choice NOUN cana-844 114 17 . . PUNCT cana-844 115 1 conventional conventional ADJ cana-844 115 2 techniques technique NOUN cana-844 115 3 for for ADP cana-844 115 4 mgmt mgmt NOUN cana-844 115 5 status status NOUN cana-844 115 6 determination determination NOUN cana-844 115 7 entail entail VERB cana-844 115 8 invasive invasive ADJ cana-844 115 9 tissue tissue NOUN cana-844 115 10 examination examination NOUN cana-844 115 11 . . PUNCT cana-844 116 1 the the DET cana-844 116 2 study study NOUN cana-844 116 3 employs employ VERB cana-844 116 4 the the DET cana-844 116 5 brain brain NOUN cana-844 116 6 tumor tumor NOUN cana-844 116 7 segmentation segmentation NOUN cana-844 116 8 ( ( PUNCT cana-844 116 9 brats brat NOUN cana-844 116 10 ) ) PUNCT cana-844 116 11 2021 2021 NUM cana-844 116 12 dataset dataset VERB cana-844 116 13 to to PART cana-844 116 14 compare compare VERB cana-844 116 15 classification classification NOUN cana-844 116 16 methods method NOUN cana-844 116 17 based base VERB cana-844 116 18 on on ADP cana-844 116 19 voxels voxel NOUN cana-844 116 20 , , PUNCT cana-844 116 21 slices slice NOUN cana-844 116 22 , , PUNCT cana-844 116 23 and and CCONJ cana-844 116 24 the the DET cana-844 116 25 entire entire ADJ cana-844 116 26 brain brain NOUN cana-844 116 27 . . PUNCT cana-844 117 1 the the DET cana-844 117 2 accuracy accuracy NOUN cana-844 117 3 of of ADP cana-844 117 4 the the DET cana-844 117 5 voxelwise voxelwise ADJ cana-844 117 6 method method NOUN cana-844 117 7 was be AUX cana-844 117 8 56.84 56.84 NUM cana-844 117 9 % % NOUN cana-844 117 10 ( ( PUNCT cana-844 117 11 sd sd ADP cana-844 117 12 4.38 4.38 NUM cana-844 117 13 % % NOUN cana-844 117 14 ) ) PUNCT cana-844 117 15 , , PUNCT cana-844 117 16 but but CCONJ cana-844 117 17 the the DET cana-844 117 18 accuracy accuracy NOUN cana-844 117 19 of of ADP cana-844 117 20 the the DET cana-844 117 21 slice slice NOUN cana-844 117 22 - - PUNCT cana-844 117 23 wise wise ADJ cana-844 117 24 and and CCONJ cana-844 117 25 whole whole ADJ cana-844 117 26 - - PUNCT cana-844 117 27 brain brain NOUN cana-844 117 28 approaches approach NOUN cana-844 117 29 was be AUX cana-844 117 30 61.37 61.37 NUM cana-844 117 31 % % NOUN cana-844 117 32 ( ( PUNCT cana-844 117 33 sd sd NOUN cana-844 117 34 1.48 1.48 NUM cana-844 117 35 % % NOUN cana-844 117 36 ) ) PUNCT cana-844 117 37 and and CCONJ cana-844 117 38 65.42 65.42 NUM cana-844 117 39 % % NOUN cana-844 117 40 ( ( PUNCT cana-844 117 41 sd sd NOUN cana-844 117 42 3.97 3.97 NUM cana-844 117 43 % % NOUN cana-844 117 44 ) ) PUNCT cana-844 117 45 , , PUNCT cana-844 117 46 respectively respectively ADV cana-844 117 47 [ [ X cana-844 117 48 11 11 NUM cana-844 117 49 ] ] PUNCT cana-844 117 50 . . PUNCT cana-844 118 1 accurate accurate ADJ cana-844 118 2 predictive predictive ADJ cana-844 118 3 models model NOUN cana-844 118 4 are be AUX cana-844 118 5 essential essential ADJ cana-844 118 6 for for ADP cana-844 118 7 clinical clinical ADJ cana-844 118 8 decision decision NOUN cana-844 118 9 - - PUNCT cana-844 118 10 making making NOUN cana-844 118 11 , , PUNCT cana-844 118 12 as as SCONJ cana-844 118 13 evidenced evidence VERB cana-844 118 14 by by ADP cana-844 118 15 the the DET cana-844 118 16 discovery discovery NOUN cana-844 118 17 of of ADP cana-844 118 18 mgmt mgmt PROPN cana-844 118 19 promoter promoter NOUN cana-844 118 20 methylation methylation NOUN cana-844 118 21 as as ADP cana-844 118 22 a a DET cana-844 118 23 critical critical ADJ cana-844 118 24 prognostic prognostic ADJ cana-844 118 25 marker marker NOUN cana-844 118 26 . . PUNCT cana-844 119 1 ai ai PROPN cana-844 119 2 has have VERB cana-844 119 3 the the DET cana-844 119 4 potential potential NOUN cana-844 119 5 to to PART cana-844 119 6 improve improve VERB cana-844 119 7 medical medical ADJ cana-844 119 8 decision decision NOUN cana-844 119 9 support support NOUN cana-844 119 10 by by ADP cana-844 119 11 utilizing utilize VERB cana-844 119 12 technological technological ADJ cana-844 119 13 breakthroughs breakthrough NOUN cana-844 119 14 , , PUNCT cana-844 119 15 but but CCONJ cana-844 119 16 integrating integrate VERB cana-844 119 17 ai ai VERB cana-844 119 18 with with ADP cana-844 119 19 electronic electronic ADJ cana-844 119 20 health health NOUN cana-844 119 21 records record NOUN cana-844 119 22 ( ( PUNCT cana-844 119 23 ehrs ehrs INTJ cana-844 119 24 ) ) PUNCT cana-844 119 25 is be AUX cana-844 119 26 still still ADV cana-844 119 27 challenging challenge VERB cana-844 119 28 work work NOUN cana-844 119 29 . . PUNCT cana-844 120 1 the the DET cana-844 120 2 abundance abundance NOUN cana-844 120 3 of of ADP cana-844 120 4 healthcare healthcare PROPN cana-844 120 5 data datum NOUN cana-844 120 6 available available ADJ cana-844 120 7 now now ADV cana-844 120 8 facilitates facilitate VERB cana-844 120 9 individualized individualized ADJ cana-844 120 10 treatment treatment NOUN cana-844 120 11 techniques technique NOUN cana-844 120 12 through through ADP cana-844 120 13 precision precision NOUN cana-844 120 14 medicine medicine NOUN cana-844 120 15 . . PUNCT cana-844 121 1 in in ADP cana-844 121 2 order order NOUN cana-844 121 3 to to PART cana-844 121 4 overcome overcome VERB cana-844 121 5 these these DET cana-844 121 6 difficulties difficulty NOUN cana-844 121 7 , , PUNCT cana-844 121 8 this this DET cana-844 121 9 work work NOUN cana-844 121 10 uses use VERB cana-844 121 11 transfer transfer NOUN cana-844 121 12 learning learn VERB cana-844 121 13 to to PART cana-844 121 14 train train VERB cana-844 121 15 models model NOUN cana-844 121 16 on on ADP cana-844 121 17 magnetic magnetic ADJ cana-844 121 18 resonance resonance NOUN cana-844 121 19 imaging imaging NOUN cana-844 121 20 ( ( PUNCT cana-844 121 21 mri mri NOUN cana-844 121 22 ) ) PUNCT cana-844 121 23 in in ADP cana-844 121 24 order order NOUN cana-844 121 25 to to PART cana-844 121 26 identify identify VERB cana-844 121 27 mgmt mgmt ADJ cana-844 121 28 promoter promoter NOUN cana-844 121 29 methylation methylation NOUN cana-844 121 30 in in ADP cana-844 121 31 glioblastoma glioblastoma NOUN cana-844 121 32 [ [ X cana-844 121 33 12 12 NUM cana-844 121 34 ] ] PUNCT cana-844 121 35 . . PUNCT cana-844 122 1 the the DET cana-844 122 2 authors author NOUN cana-844 122 3 of of ADP cana-844 122 4 this this DET cana-844 122 5 study study NOUN cana-844 122 6 [ [ X cana-844 122 7 13 13 NUM cana-844 122 8 ] ] PUNCT cana-844 122 9 developed develop VERB cana-844 122 10 a a DET cana-844 122 11 brand brand NOUN cana-844 122 12 - - PUNCT cana-844 122 13 new new ADJ cana-844 122 14 two two NUM cana-844 122 15 - - PUNCT cana-844 122 16 stage stage NOUN cana-844 122 17 mgmt mgmt NOUN cana-844 122 18 promoter promoter NOUN cana-844 122 19 methylation methylation NOUN cana-844 122 20 prediction prediction NOUN cana-844 122 21 ( ( PUNCT cana-844 122 22 mgmt mgmt NOUN cana-844 122 23 - - PUNCT cana-844 122 24 pmp pmp NOUN cana-844 122 25 ) ) PUNCT cana-844 122 26 method method NOUN cana-844 122 27 with with ADP cana-844 122 28 the the DET cana-844 122 29 goal goal NOUN cana-844 122 30 of of ADP cana-844 122 31 precisely precisely ADV cana-844 122 32 identifying identify VERB cana-844 122 33 glioblastoma glioblastoma ADJ cana-844 122 34 genetic genetic ADJ cana-844 122 35 subgroups subgroup NOUN cana-844 122 36 . . PUNCT cana-844 123 1 in in ADP cana-844 123 2 order order NOUN cana-844 123 3 to to PART cana-844 123 4 extract extract VERB cana-844 123 5 latent latent NOUN cana-844 123 6 features feature NOUN cana-844 123 7 fused fuse VERB cana-844 123 8 with with ADP cana-844 123 9 radiomic radiomic ADJ cana-844 123 10 information information NOUN cana-844 123 11 and and CCONJ cana-844 123 12 improve improve VERB cana-844 123 13 prediction prediction NOUN cana-844 123 14 capabilities capability NOUN cana-844 123 15 , , PUNCT cana-844 123 16 this this DET cana-844 123 17 method method NOUN cana-844 123 18 integrates integrate VERB cana-844 123 19 a a DET cana-844 123 20 deep deep ADJ cana-844 123 21 learning learn VERB cana-844 123 22 radiomic radiomic ADJ cana-844 123 23 feature feature NOUN cana-844 123 24 extraction extraction NOUN cana-844 123 25 module module NOUN cana-844 123 26 . . PUNCT cana-844 124 1 to to PART cana-844 124 2 improve improve VERB cana-844 124 3 model model NOUN cana-844 124 4 performance performance NOUN cana-844 124 5 , , PUNCT cana-844 124 6 the the DET cana-844 124 7 authors author NOUN cana-844 124 8 successfully successfully ADV cana-844 124 9 isolated isolate VERB cana-844 124 10 negative negative ADJ cana-844 124 11 training training NOUN cana-844 124 12 cases case NOUN cana-844 124 13 using use VERB cana-844 124 14 a a DET cana-844 124 15 novice novice NOUN cana-844 124 16 rejection rejection NOUN cana-844 124 17 strategy strategy NOUN cana-844 124 18 . . PUNCT cana-844 125 1 evaluations evaluation NOUN cana-844 125 2 on on ADP cana-844 125 3 the the DET cana-844 125 4 2021 2021 NUM cana-844 125 5 rsna rsna NOUN cana-844 125 6 brain brain NOUN cana-844 125 7 tumor tumor NOUN cana-844 125 8 challenge challenge NOUN cana-844 125 9 dataset dataset NOUN cana-844 125 10 show show VERB cana-844 125 11 exceptional exceptional ADJ cana-844 125 12 performance performance NOUN cana-844 125 13 in in ADP cana-844 125 14 terms term NOUN cana-844 125 15 of of ADP cana-844 125 16 classification classification NOUN cana-844 125 17 , , PUNCT cana-844 125 18 with with ADP cana-844 125 19 96.84 96.84 NUM cana-844 125 20 % % NOUN cana-844 125 21 accuracy accuracy NOUN cana-844 125 22 , , PUNCT cana-844 125 23 96.08 96.08 NUM cana-844 125 24 % % NOUN cana-844 125 25 sensitivity sensitivity NOUN cana-844 125 26 , , PUNCT cana-844 125 27 and and CCONJ cana-844 125 28 97.44 97.44 NUM cana-844 125 29 % % NOUN cana-844 125 30 specificity specificity NOUN cana-844 125 31 in in ADP cana-844 125 32 mgmt mgmt PROPN cana-844 125 33 methylation methylation PROPN cana-844 125 34 status status NOUN cana-844 125 35 detection detection NOUN cana-844 125 36 accomplished accomplish VERB cana-844 125 37 . . PUNCT cana-844 126 1 with with ADP cana-844 126 2 the the DET cana-844 126 3 help help NOUN cana-844 126 4 of of ADP cana-844 126 5 t2 t2 NOUN cana-844 126 6 - - PUNCT cana-844 126 7 w w NOUN cana-844 126 8 magnetic magnetic ADJ cana-844 126 9 resonance resonance NOUN cana-844 126 10 imaging imaging NOUN cana-844 126 11 ( ( PUNCT cana-844 126 12 mri mri NOUN cana-844 126 13 ) ) PUNCT cana-844 126 14 , , PUNCT cana-844 126 15 a a DET cana-844 126 16 deep deep ADJ cana-844 126 17 learning learning NOUN cana-844 126 18 network network NOUN cana-844 126 19 called call VERB cana-844 126 20 mgmtnet mgmtnet NOUN cana-844 126 21 was be AUX cana-844 126 22 created create VERB cana-844 126 23 specifically specifically ADV cana-844 126 24 for for ADP cana-844 126 25 this this DET cana-844 126 26 study study NOUN cana-844 126 27 in in ADP cana-844 126 28 order order NOUN cana-844 126 29 to to PART cana-844 126 30 assess assess VERB cana-844 126 31 the the DET cana-844 126 32 methylation methylation NOUN cana-844 126 33 status status NOUN cana-844 126 34 of of ADP cana-844 126 35 the the DET cana-844 126 36 o6methylguanine o6methylguanine NOUN cana-844 126 37 - - PUNCT cana-844 126 38 dna dna NOUN cana-844 126 39 methyltransferase methyltransferase NOUN cana-844 126 40 ( ( PUNCT cana-844 126 41 mgmt mgmt NOUN cana-844 126 42 ) ) PUNCT cana-844 126 43 promoter promoter NOUN cana-844 126 44 in in ADP cana-844 126 45 gliomas glioma NOUN cana-844 126 46 . . PUNCT cana-844 127 1 the the DET cana-844 127 2 network network NOUN cana-844 127 3 was be AUX cana-844 127 4 able able ADJ cana-844 127 5 to to PART cana-844 127 6 predict predict VERB cana-844 127 7 the the DET cana-844 127 8 mgmt mgmt PROPN cana-844 127 9 methylation methylation PROPN cana-844 127 10 status status NOUN cana-844 127 11 of of ADP cana-844 127 12 247 247 NUM cana-844 127 13 participants participant NOUN cana-844 127 14 with with ADP cana-844 127 15 a a DET cana-844 127 16 mean mean ADJ cana-844 127 17 cross cross ADJ cana-844 127 18 - - ADJ cana-844 127 19 validation validation ADJ cana-844 127 20 accuracy accuracy NOUN cana-844 127 21 of of ADP cana-844 127 22 94.73 94.73 NUM cana-844 127 23 % % NOUN cana-844 127 24 , , PUNCT cana-844 127 25 sensitivity sensitivity NOUN cana-844 127 26 of of ADP cana-844 127 27 96.31 96.31 NUM cana-844 127 28 % % NOUN cana-844 127 29 , , PUNCT cana-844 127 30 and and CCONJ cana-844 127 31 specificity specificity NOUN cana-844 127 32 of of ADP cana-844 127 33 91.66 91.66 NUM cana-844 127 34 % % NOUN cana-844 127 35 by by ADP cana-844 127 36 using use VERB cana-844 127 37 brain brain NOUN cana-844 127 38 mri mri NOUN cana-844 127 39 and and CCONJ cana-844 127 40 genetic genetic ADJ cana-844 127 41 data datum NOUN cana-844 127 42 . . PUNCT cana-844 128 1 furthermore furthermore ADV cana-844 128 2 , , PUNCT cana-844 128 3 the the DET cana-844 128 4 network network NOUN cana-844 128 5 attained attain VERB cana-844 128 6 a a DET cana-844 128 7 mean mean ADJ cana-844 128 8 dice dice NOUN cana-844 128 9 - - PUNCT cana-844 128 10 score score NOUN cana-844 128 11 of of ADP cana-844 128 12 0.82 0.82 NUM cana-844 128 13 and and CCONJ cana-844 128 14 a a DET cana-844 128 15 mean mean ADJ cana-844 128 16 auc auc NOUN cana-844 128 17 of of ADP cana-844 128 18 0.93 0.93 NUM cana-844 128 19 for for ADP cana-844 128 20 whole whole ADJ cana-844 128 21 tumor tumor NOUN cana-844 128 22 segmentation segmentation NOUN cana-844 128 23 [ [ X cana-844 128 24 14 14 NUM cana-844 128 25 ] ] SYM cana-844 128 26 . . PUNCT cana-844 129 1 3 3 X cana-844 129 2 . . X cana-844 129 3 methodology methodology NOUN cana-844 129 4 this this DET cana-844 129 5 section section NOUN cana-844 129 6 introduces introduce VERB cana-844 129 7 the the DET cana-844 129 8 suggested suggest VERB cana-844 129 9 approach approach NOUN cana-844 129 10 for for ADP cana-844 129 11 classifying classify VERB cana-844 129 12 brain brain NOUN cana-844 129 13 tumors tumor NOUN cana-844 129 14 using use VERB cana-844 129 15 deep deep ADJ cana-844 129 16 learning learning NOUN cana-844 129 17 across across ADP cana-844 129 18 multiple multiple ADJ cana-844 129 19 modes mode NOUN cana-844 129 20 . . PUNCT cana-844 130 1 the the DET cana-844 130 2 method method NOUN cana-844 130 3 proposed propose VERB cana-844 130 4 includes include VERB cana-844 130 5 five five NUM cana-844 130 6 main main ADJ cana-844 130 7 stepsdata stepsdata NOUN cana-844 130 8 pre pre ADJ cana-844 130 9 - - ADJ cana-844 130 10 processing processing ADJ cana-844 130 11 , , PUNCT cana-844 130 12 feature feature NOUN cana-844 130 13 communications communication NOUN cana-844 130 14 on on ADP cana-844 130 15 applied apply VERB cana-844 130 16 nonlinear nonlinear ADJ cana-844 130 17 analysis analysis NOUN cana-844 130 18 issn issn NOUN cana-844 130 19 : : PUNCT cana-844 130 20 1074 1074 NUM cana-844 130 21 - - PUNCT cana-844 130 22 133x 133x NUM cana-844 130 23 vol vol NOUN cana-844 130 24 31 31 NUM cana-844 130 25 no no NOUN cana-844 130 26 . . PUNCT cana-844 131 1 4s 4s NUM cana-844 131 2 ( ( PUNCT cana-844 131 3 2024 2024 NUM cana-844 131 4 ) ) PUNCT cana-844 131 5 236 236 NUM cana-844 131 6 https://internationalpubls.com https://internationalpubls.com X cana-844 131 7 extraction extraction NOUN cana-844 131 8 , , PUNCT cana-844 131 9 feature feature NOUN cana-844 131 10 selection selection NOUN cana-844 131 11 , , PUNCT cana-844 131 12 training training NOUN cana-844 131 13 and and CCONJ cana-844 131 14 testing test VERB cana-844 131 15 the the DET cana-844 131 16 selected select VERB cana-844 131 17 features feature NOUN cana-844 131 18 on on ADP cana-844 131 19 machine machine NOUN cana-844 131 20 learning learn VERB cana-844 131 21 techniques technique NOUN cana-844 131 22 and and CCONJ cana-844 131 23 saving save VERB cana-844 131 24 the the DET cana-844 131 25 model model NOUN cana-844 131 26 for for ADP cana-844 131 27 future future ADJ cana-844 131 28 predictions prediction NOUN cana-844 131 29 . . PUNCT cana-844 132 1 the the DET cana-844 132 2 procedure procedure NOUN cana-844 132 3 starts start VERB cana-844 132 4 with with ADP cana-844 132 5 a a DET cana-844 132 6 thorough thorough ADJ cana-844 132 7 preliminary preliminary ADJ cana-844 132 8 processing processing NOUN cana-844 132 9 of of ADP cana-844 132 10 the the DET cana-844 132 11 data datum NOUN cana-844 132 12 to to PART cana-844 132 13 adjust adjust VERB cana-844 132 14 image image NOUN cana-844 132 15 sizes size NOUN cana-844 132 16 , , PUNCT cana-844 132 17 normalise normalise PROPN cana-844 132 18 characteristics characteristic NOUN cana-844 132 19 , , PUNCT cana-844 132 20 and and CCONJ cana-844 132 21 solve solve VERB cana-844 132 22 the the DET cana-844 132 23 issue issue NOUN cana-844 132 24 of of ADP cana-844 132 25 unbalanced unbalanced ADJ cana-844 132 26 classes class NOUN cana-844 132 27 . . PUNCT cana-844 133 1 subsequently subsequently ADV cana-844 133 2 , , PUNCT cana-844 133 3 detailed detailed ADJ cana-844 133 4 characteristics characteristic NOUN cana-844 133 5 are be AUX cana-844 133 6 extracted extract VERB cana-844 133 7 from from ADP cana-844 133 8 the the DET cana-844 133 9 processed process VERB cana-844 133 10 information information NOUN cana-844 133 11 using use VERB cana-844 133 12 pre pre ADJ cana-844 133 13 - - ADJ cana-844 133 14 trained train VERB cana-844 133 15 vgg19 vgg19 NOUN cana-844 133 16 and and CCONJ cana-844 133 17 resnet50 resnet50 NOUN cana-844 133 18 models model NOUN cana-844 133 19 , , PUNCT cana-844 133 20 which which PRON cana-844 133 21 capture capture VERB cana-844 133 22 complex complex ADJ cana-844 133 23 patterns pattern NOUN cana-844 133 24 . . PUNCT cana-844 134 1 then then ADV cana-844 134 2 , , PUNCT cana-844 134 3 to to PART cana-844 134 4 help help VERB cana-844 134 5 with with ADP cana-844 134 6 dimensionality dimensionality NOUN cana-844 134 7 reduction reduction NOUN cana-844 134 8 , , PUNCT cana-844 134 9 the the DET cana-844 134 10 random random ADJ cana-844 134 11 forest forest NOUN cana-844 134 12 feature feature NOUN cana-844 134 13 selector selector NOUN cana-844 134 14 identifies identify VERB cana-844 134 15 the the DET cana-844 134 16 most most ADV cana-844 134 17 meaningful meaningful ADJ cana-844 134 18 features feature NOUN cana-844 134 19 . . PUNCT cana-844 135 1 ultimately ultimately ADV cana-844 135 2 , , PUNCT cana-844 135 3 the the DET cana-844 135 4 characteristics characteristic NOUN cana-844 135 5 that that PRON cana-844 135 6 were be AUX cana-844 135 7 selected select VERB cana-844 135 8 are be AUX cana-844 135 9 classified classify VERB cana-844 135 10 by by ADP cana-844 135 11 supervised supervised ADJ cana-844 135 12 algorithms algorithm NOUN cana-844 135 13 for for ADP cana-844 135 14 machine machine NOUN cana-844 135 15 learning learning NOUN cana-844 135 16 such such ADJ cana-844 135 17 as as ADP cana-844 135 18 knn knn PROPN cana-844 135 19 , , PUNCT cana-844 135 20 naive naive ADJ cana-844 135 21 bayes bayes NOUN cana-844 135 22 , , PUNCT cana-844 135 23 random random ADJ cana-844 135 24 forest forest NOUN cana-844 135 25 , , PUNCT cana-844 135 26 logistic logistic ADJ cana-844 135 27 regression regression NOUN cana-844 135 28 , , PUNCT cana-844 135 29 and and CCONJ cana-844 135 30 sequential sequential ADJ cana-844 135 31 fcnet fcnet PROPN cana-844 135 32 ann ann PROPN cana-844 135 33 , , PUNCT cana-844 135 34 which which PRON cana-844 135 35 provide provide VERB cana-844 135 36 accurate accurate ADJ cana-844 135 37 estimations estimation NOUN cana-844 135 38 of of ADP cana-844 135 39 the the DET cana-844 135 40 target target NOUN cana-844 135 41 labels label NOUN cana-844 135 42 . . PUNCT cana-844 136 1 fig fig NOUN cana-844 136 2 1 1 NUM cana-844 136 3 illustrates illustrate VERB cana-844 136 4 the the DET cana-844 136 5 architecture architecture NOUN cana-844 136 6 for for ADP cana-844 136 7 brain brain NOUN cana-844 136 8 tumor tumor NOUN cana-844 136 9 radiogenomic radiogenomic ADJ cana-844 136 10 classification classification NOUN cana-844 136 11 to to PART cana-844 136 12 predict predict VERB cana-844 136 13 the the DET cana-844 136 14 status status NOUN cana-844 136 15 of of ADP cana-844 136 16 genetic genetic ADJ cana-844 136 17 biomarker biomarker NOUN cana-844 136 18 . . PUNCT cana-844 137 1 fig fig NOUN cana-844 137 2 1 1 NUM cana-844 137 3 : : PUNCT cana-844 137 4 proposed propose VERB cana-844 137 5 architecture architecture NOUN cana-844 137 6 for for ADP cana-844 137 7 brain brain NOUN cana-844 137 8 tumor tumor NOUN cana-844 137 9 radiogenomic radiogenomic ADJ cana-844 137 10 classification classification NOUN cana-844 137 11 3.1 3.1 NUM cana-844 137 12 dataset dataset NOUN cana-844 137 13 description description NOUN cana-844 137 14 using use VERB cana-844 137 15 magnetic magnetic ADJ cana-844 137 16 resonance resonance NOUN cana-844 137 17 imaging imaging NOUN cana-844 137 18 ( ( PUNCT cana-844 137 19 mri mri NOUN cana-844 137 20 ) ) PUNCT cana-844 137 21 scans scan NOUN cana-844 137 22 , , PUNCT cana-844 137 23 the the DET cana-844 137 24 rsna rsna PROPN cana-844 137 25 miccai miccai PROPN cana-844 137 26 brain brain PROPN cana-844 137 27 tumour tumour NOUN cana-844 137 28 segmentation segmentation NOUN cana-844 137 29 ( ( PUNCT cana-844 137 30 brats brat NOUN cana-844 137 31 ) ) PUNCT cana-844 137 32 2021 2021 NUM cana-844 137 33 challenge challenge NOUN cana-844 137 34 aims aim VERB cana-844 137 35 to to PART cana-844 137 36 predict predict VERB cana-844 137 37 one one NUM cana-844 137 38 of of ADP cana-844 137 39 the the DET cana-844 137 40 common common ADJ cana-844 137 41 genetic genetic ADJ cana-844 137 42 features feature NOUN cana-844 137 43 of of ADP cana-844 137 44 glioblastoma glioblastoma NOUN cana-844 137 45 ( ( PUNCT cana-844 137 46 mgmt mgmt NOUN cana-844 137 47 promoter promoter NOUN cana-844 137 48 methylation methylation NOUN cana-844 137 49 status status NOUN cana-844 137 50 ) ) PUNCT cana-844 137 51 from from ADP cana-844 137 52 pre pre ADJ cana-844 137 53 - - ADJ cana-844 137 54 operative operative ADJ cana-844 137 55 scans scan NOUN cana-844 137 56 using use VERB cana-844 137 57 mri mri NOUN cana-844 137 58 as as ADV cana-844 137 59 well well ADV cana-844 137 60 as as ADP cana-844 137 61 automate automate ADJ cana-844 137 62 tumour tumour NOUN cana-844 137 63 subregion subregion NOUN cana-844 137 64 segmentation segmentation NOUN cana-844 137 65 . . PUNCT cana-844 138 1 the the DET cana-844 138 2 training training NOUN cana-844 138 3 cohort cohort NOUN cana-844 138 4 's 's PART cana-844 138 5 organisational organisational ADJ cana-844 138 6 structure structure NOUN cana-844 138 7 is be AUX cana-844 138 8 as as SCONJ cana-844 138 9 follows follow VERB cana-844 138 10 : : PUNCT cana-844 138 11 every every DET cana-844 138 12 single single ADJ cana-844 138 13 case case NOUN cana-844 138 14 has have VERB cana-844 138 15 its its PRON cana-844 138 16 own own ADJ cana-844 138 17 folder folder NOUN cana-844 138 18 , , PUNCT cana-844 138 19 identified identify VERB cana-844 138 20 by by ADP cana-844 138 21 a a DET cana-844 138 22 five five NUM cana-844 138 23 - - PUNCT cana-844 138 24 digit digit NOUN cana-844 138 25 number number NOUN cana-844 138 26 . . PUNCT cana-844 139 1 each each PRON cana-844 139 2 of of ADP cana-844 139 3 the the DET cana-844 139 4 aforementioned aforementioned ADJ cana-844 139 5 " " PUNCT cana-844 139 6 case case NOUN cana-844 139 7 " " PUNCT cana-844 139 8 folders folder NOUN cana-844 139 9 contains contain VERB cana-844 139 10 four four NUM cana-844 139 11 sub sub NOUN cana-844 139 12 - - NOUN cana-844 139 13 files file NOUN cana-844 139 14 , , PUNCT cana-844 139 15 one one NUM cana-844 139 16 containing contain VERB cana-844 139 17 each each PRON cana-844 139 18 of of ADP cana-844 139 19 the the DET cana-844 139 20 anatomical anatomical ADJ cana-844 139 21 multi multi ADJ cana-844 139 22 - - ADJ cana-844 139 23 parametric parametric ADJ cana-844 139 24 mri mri NOUN cana-844 139 25 scans scan NOUN cana-844 139 26 in in ADP cana-844 139 27 dicom dicom PROPN cana-844 139 28 standard standard ADJ cana-844 139 29 format format NOUN cana-844 139 30 . . PUNCT cana-844 140 1 the the DET cana-844 140 2 following follow VERB cana-844 140 3 specific specific ADJ cana-844 140 4 scans scan NOUN cana-844 140 5 are be AUX cana-844 140 6 included include VERB cana-844 140 7 : : PUNCT cana-844 140 8 pre pre ADJ cana-844 140 9 - - ADJ cana-844 140 10 contrast contrast ADJ cana-844 140 11 t1 t1 NOUN cana-844 140 12 - - PUNCT cana-844 140 13 weighted weighted ADJ cana-844 140 14 ( ( PUNCT cana-844 140 15 t1w t1w NUM cana-844 140 16 ) ) PUNCT cana-844 140 17 , , PUNCT cana-844 140 18 post post ADJ cana-844 140 19 - - ADJ cana-844 140 20 contrast contrast ADJ cana-844 140 21 t1 t1 NOUN cana-844 140 22 - - PUNCT cana-844 140 23 weighted weighted ADJ cana-844 140 24 ( ( PUNCT cana-844 140 25 t1gd t1gd NOUN cana-844 140 26 ) ) PUNCT cana-844 140 27 , , PUNCT cana-844 140 28 flair flair NOUN cana-844 140 29 stands stand VERB cana-844 140 30 for for ADP cana-844 140 31 fluid fluid ADJ cana-844 140 32 attenuated attenuate VERB cana-844 140 33 inversion inversion NOUN cana-844 140 34 recovery recovery NOUN cana-844 140 35 , , PUNCT cana-844 140 36 and and CCONJ cana-844 140 37 t2 t2 NOUN cana-844 140 38 - - PUNCT cana-844 140 39 weighted weight VERB cana-844 140 40 there there PRON cana-844 140 41 are be VERB cana-844 140 42 585 585 NUM cana-844 140 43 entries entry NOUN cana-844 140 44 in in ADP cana-844 140 45 the the DET cana-844 140 46 training training NOUN cana-844 140 47 data datum NOUN cana-844 140 48 , , PUNCT cana-844 140 49 each each PRON cana-844 140 50 of of ADP cana-844 140 51 which which PRON cana-844 140 52 represents represent VERB cana-844 140 53 a a DET cana-844 140 54 particular particular ADJ cana-844 140 55 individual individual NOUN cana-844 140 56 or or CCONJ cana-844 140 57 subject subject ADJ cana-844 140 58 . . PUNCT cana-844 141 1 the the DET cana-844 141 2 distribution distribution NOUN cana-844 141 3 of of ADP cana-844 141 4 class class NOUN cana-844 141 5 labels label NOUN cana-844 141 6 for for ADP cana-844 141 7 training training NOUN cana-844 141 8 data datum NOUN cana-844 141 9 is be AUX cana-844 141 10 shown show VERB cana-844 141 11 in in ADP cana-844 141 12 fig.2 fig.2 PROPN cana-844 141 13 . . PUNCT cana-844 142 1 communications communication NOUN cana-844 142 2 on on ADP cana-844 142 3 applied apply VERB cana-844 142 4 nonlinear nonlinear ADJ cana-844 142 5 analysis analysis NOUN cana-844 142 6 issn issn NOUN cana-844 142 7 : : PUNCT cana-844 142 8 1074 1074 NUM cana-844 142 9 - - PUNCT cana-844 142 10 133x 133x NUM cana-844 142 11 vol vol NOUN cana-844 142 12 31 31 NUM cana-844 142 13 no no NOUN cana-844 142 14 . . PUNCT cana-844 143 1 4s 4s NUM cana-844 143 2 ( ( PUNCT cana-844 143 3 2024 2024 NUM cana-844 143 4 ) ) PUNCT cana-844 143 5 237 237 NUM cana-844 143 6 https://internationalpubls.com https://internationalpubls.com X cana-844 143 7 fig fig NOUN cana-844 143 8 2 2 NUM cana-844 143 9 : : PUNCT cana-844 143 10 distribution distribution NOUN cana-844 143 11 of of ADP cana-844 143 12 class class NOUN cana-844 143 13 labels label NOUN cana-844 143 14 for for ADP cana-844 143 15 training training NOUN cana-844 143 16 data datum NOUN cana-844 143 17 3.2 3.2 NUM cana-844 143 18 data datum NOUN cana-844 143 19 pre pre ADJ cana-844 143 20 - - ADJ cana-844 143 21 processing processing ADJ cana-844 143 22 data datum NOUN cana-844 143 23 pre pre ADJ cana-844 143 24 - - ADJ cana-844 143 25 processing processing NOUN cana-844 143 26 is be AUX cana-844 143 27 a a DET cana-844 143 28 crucial crucial ADJ cana-844 143 29 initial initial ADJ cana-844 143 30 step step NOUN cana-844 143 31 in in ADP cana-844 143 32 preparing prepare VERB cana-844 143 33 brain brain NOUN cana-844 143 34 tumour tumour NOUN cana-844 143 35 datasets dataset NOUN cana-844 143 36 for for ADP cana-844 143 37 efficient efficient ADJ cana-844 143 38 machine machine NOUN cana-844 143 39 learning learn VERB cana-844 143 40 algorithm algorithm NOUN cana-844 143 41 training training NOUN cana-844 143 42 . . PUNCT cana-844 144 1 in in ADP cana-844 144 2 order order NOUN cana-844 144 3 to to PART cana-844 144 4 guarantee guarantee VERB cana-844 144 5 dataset dataset ADJ cana-844 144 6 integrity integrity NOUN cana-844 144 7 and and CCONJ cana-844 144 8 resilience resilience NOUN cana-844 144 9 , , PUNCT cana-844 144 10 this this DET cana-844 144 11 work work NOUN cana-844 144 12 proposes propose VERB cana-844 144 13 a a DET cana-844 144 14 methodical methodical ADJ cana-844 144 15 strategy strategy NOUN cana-844 144 16 that that PRON cana-844 144 17 includes include VERB cana-844 144 18 image image NOUN cana-844 144 19 loading loading NOUN cana-844 144 20 , , PUNCT cana-844 144 21 scaling scaling NOUN cana-844 144 22 , , PUNCT cana-844 144 23 normalisation normalisation NOUN cana-844 144 24 , , PUNCT cana-844 144 25 augmentation augmentation NOUN cana-844 144 26 , , PUNCT cana-844 144 27 and and CCONJ cana-844 144 28 the the DET cana-844 144 29 remedy remedy NOUN cana-844 144 30 of of ADP cana-844 144 31 data datum NOUN cana-844 144 32 imbalances imbalance NOUN cana-844 144 33 . . PUNCT cana-844 145 1 in in ADP cana-844 145 2 the the DET cana-844 145 3 field field NOUN cana-844 145 4 of of ADP cana-844 145 5 machine machine NOUN cana-844 145 6 learning learning NOUN cana-844 145 7 , , PUNCT cana-844 145 8 random random ADJ cana-844 145 9 oversampling oversampling NOUN cana-844 145 10 is be AUX cana-844 145 11 a a DET cana-844 145 12 strategy strategy NOUN cana-844 145 13 that that PRON cana-844 145 14 addresses address VERB cana-844 145 15 imbalances imbalance NOUN cana-844 145 16 in in ADP cana-844 145 17 class class NOUN cana-844 145 18 by by ADP cana-844 145 19 randomly randomly ADV cana-844 145 20 replicating replicate VERB cana-844 145 21 instances instance NOUN cana-844 145 22 of of ADP cana-844 145 23 minority minority NOUN cana-844 145 24 classes class NOUN cana-844 145 25 until until SCONJ cana-844 145 26 an an DET cana-844 145 27 even even ADJ cana-844 145 28 distribution distribution NOUN cana-844 145 29 has have AUX cana-844 145 30 been be AUX cana-844 145 31 obtained obtain VERB cana-844 145 32 . . PUNCT cana-844 146 1 in in ADP cana-844 146 2 order order NOUN cana-844 146 3 to to PART cana-844 146 4 increase increase VERB cana-844 146 5 the the DET cana-844 146 6 minority minority NOUN cana-844 146 7 class class NOUN cana-844 146 8 's 's PART cana-844 146 9 presence presence NOUN cana-844 146 10 in in ADP cana-844 146 11 the the DET cana-844 146 12 dataset dataset NOUN cana-844 146 13 , , PUNCT cana-844 146 14 it it PRON cana-844 146 15 replicates replicate VERB cana-844 146 16 instances instance NOUN cana-844 146 17 that that PRON cana-844 146 18 are be AUX cana-844 146 19 chosen choose VERB cana-844 146 20 at at ADP cana-844 146 21 random random ADJ cana-844 146 22 from from ADP cana-844 146 23 the the DET cana-844 146 24 minority minority NOUN cana-844 146 25 class class NOUN cana-844 146 26 . . PUNCT cana-844 147 1 because because SCONJ cana-844 147 2 this this DET cana-844 147 3 strategy strategy NOUN cana-844 147 4 simply simply ADV cana-844 147 5 replicates replicate VERB cana-844 147 6 data datum NOUN cana-844 147 7 points point NOUN cana-844 147 8 that that PRON cana-844 147 9 already already ADV cana-844 147 10 exist exist VERB cana-844 147 11 , , PUNCT cana-844 147 12 it it PRON cana-844 147 13 prevents prevent VERB cana-844 147 14 the the DET cana-844 147 15 development development NOUN cana-844 147 16 of of ADP cana-844 147 17 bias bias NOUN cana-844 147 18 . . PUNCT cana-844 148 1 random random ADJ cana-844 148 2 oversampling oversampling NOUN cana-844 148 3 has have VERB cana-844 148 4 the the DET cana-844 148 5 benefit benefit NOUN cana-844 148 6 of of ADP cana-844 148 7 being be AUX cana-844 148 8 straightforward straightforward ADJ cana-844 148 9 and and CCONJ cana-844 148 10 simple simple ADJ cana-844 148 11 to to PART cana-844 148 12 apply apply VERB cana-844 148 13 , , PUNCT cana-844 148 14 requiring require VERB cana-844 148 15 little little ADJ cana-844 148 16 modification modification NOUN cana-844 148 17 to to ADP cana-844 148 18 current current ADJ cana-844 148 19 methods method NOUN cana-844 148 20 . . PUNCT cana-844 149 1 furthermore furthermore ADV cana-844 149 2 , , PUNCT cana-844 149 3 by by ADP cana-844 149 4 offering offer VERB cana-844 149 5 more more ADJ cana-844 149 6 equitable equitable ADJ cana-844 149 7 training training NOUN cana-844 149 8 data datum NOUN cana-844 149 9 , , PUNCT cana-844 149 10 it it PRON cana-844 149 11 can can AUX cana-844 149 12 enhance enhance VERB cana-844 149 13 the the DET cana-844 149 14 efficiency efficiency NOUN cana-844 149 15 of of ADP cana-844 149 16 classifiers classifier NOUN cana-844 149 17 by by ADP cana-844 149 18 improving improve VERB cana-844 149 19 generalisation generalisation NOUN cana-844 149 20 and and CCONJ cana-844 149 21 lowering lower VERB cana-844 149 22 bias bias NOUN cana-844 149 23 towards towards ADP cana-844 149 24 the the DET cana-844 149 25 majority majority NOUN cana-844 149 26 class class NOUN cana-844 149 27 [ [ X cana-844 149 28 15 15 NUM cana-844 149 29 ] ] SYM cana-844 149 30 . . PUNCT cana-844 150 1 3.3 3.3 NUM cana-844 150 2 feature feature NOUN cana-844 150 3 extraction extraction NOUN cana-844 150 4 the the DET cana-844 150 5 features feature NOUN cana-844 150 6 from from ADP cana-844 150 7 the the DET cana-844 150 8 mri mri NOUN cana-844 150 9 images image NOUN cana-844 150 10 were be AUX cana-844 150 11 extracted extract VERB cana-844 150 12 using use VERB cana-844 150 13 two two NUM cana-844 150 14 deep deep ADJ cana-844 150 15 learning learning NOUN cana-844 150 16 methodologies methodology NOUN cana-844 150 17 vgg19 vgg19 VERB cana-844 150 18 and and CCONJ cana-844 150 19 resnet50 resnet50 NOUN cana-844 150 20 . . PUNCT cana-844 151 1 3.3.1 3.3.1 NUM cana-844 151 2 vgg19 vgg19 VERB cana-844 151 3 the the DET cana-844 151 4 vgg19 vgg19 NOUN cana-844 151 5 model model NOUN cana-844 151 6 is be AUX cana-844 151 7 composed compose VERB cana-844 151 8 of of ADP cana-844 151 9 16 16 NUM cana-844 151 10 convolution convolution NOUN cana-844 151 11 layers layer NOUN cana-844 151 12 , , PUNCT cana-844 151 13 19 19 NUM cana-844 151 14 relu relu NOUN cana-844 151 15 activation activation NOUN cana-844 151 16 layers layer NOUN cana-844 151 17 , , PUNCT cana-844 151 18 four four NUM cana-844 151 19 pooling pool VERB cana-844 151 20 layers layer NOUN cana-844 151 21 , , PUNCT cana-844 151 22 three three NUM cana-844 151 23 fully fully ADV cana-844 151 24 connected connected ADJ cana-844 151 25 layers layer NOUN cana-844 151 26 , , PUNCT cana-844 151 27 and and CCONJ cana-844 151 28 one one NUM cana-844 151 29 softmax softmax NOUN cana-844 151 30 layer layer NOUN cana-844 151 31 for for ADP cana-844 151 32 classification classification NOUN cana-844 151 33 . . PUNCT cana-844 152 1 by by ADP cana-844 152 2 utilizing utilize VERB cana-844 152 3 3x3 3x3 NUM cana-844 152 4 convolutional convolutional ADJ cana-844 152 5 filters filter NOUN cana-844 152 6 , , PUNCT cana-844 152 7 vgg19 vgg19 PROPN cana-844 152 8 can can AUX cana-844 152 9 detect detect VERB cana-844 152 10 complex complex ADJ cana-844 152 11 patterns pattern NOUN cana-844 152 12 and and CCONJ cana-844 152 13 features feature NOUN cana-844 152 14 within within ADP cana-844 152 15 image image NOUN cana-844 152 16 data datum NOUN cana-844 152 17 . . PUNCT cana-844 153 1 the the DET cana-844 153 2 maxpooling maxpoole VERB cana-844 153 3 layers layer NOUN cana-844 153 4 help help VERB cana-844 153 5 decrease decrease VERB cana-844 153 6 input input NOUN cana-844 153 7 dimensions dimension NOUN cana-844 153 8 , , PUNCT cana-844 153 9 reducing reduce VERB cana-844 153 10 computational computational ADJ cana-844 153 11 load load NOUN cana-844 153 12 . . PUNCT cana-844 154 1 the the DET cana-844 154 2 fully fully ADV cana-844 154 3 connected connected ADJ cana-844 154 4 layers layer NOUN cana-844 154 5 at at ADP cana-844 154 6 the the DET cana-844 154 7 end end NOUN cana-844 154 8 enable enable VERB cana-844 154 9 making make VERB cana-844 154 10 predictions prediction NOUN cana-844 154 11 based base VERB cana-844 154 12 on on ADP cana-844 154 13 the the DET cana-844 154 14 high high ADJ cana-844 154 15 - - PUNCT cana-844 154 16 level level NOUN cana-844 154 17 features feature NOUN cana-844 154 18 identified identify VERB cana-844 154 19 by by ADP cana-844 154 20 the the DET cana-844 154 21 convolutional convolutional ADJ cana-844 154 22 layers layer NOUN cana-844 154 23 . . PUNCT cana-844 155 1 vgg19 vgg19 PROPN cana-844 155 2 employs employ VERB cana-844 155 3 the the DET cana-844 155 4 relu relu NOUN cana-844 155 5 activation activation NOUN cana-844 155 6 function function NOUN cana-844 155 7 for for ADP cana-844 155 8 introducing introduce VERB cana-844 155 9 non non ADJ cana-844 155 10 - - NOUN cana-844 155 11 linearity linearity ADJ cana-844 155 12 . . PUNCT cana-844 156 1 fig fig NOUN cana-844 156 2 3 3 NUM cana-844 156 3 illustrates illustrate VERB cana-844 156 4 the the DET cana-844 156 5 architecture architecture NOUN cana-844 156 6 of of ADP cana-844 156 7 vgg19 vgg19 PROPN cana-844 156 8 . . PUNCT cana-844 157 1 communications communication NOUN cana-844 157 2 on on ADP cana-844 157 3 applied apply VERB cana-844 157 4 nonlinear nonlinear ADJ cana-844 157 5 analysis analysis NOUN cana-844 157 6 issn issn NOUN cana-844 157 7 : : PUNCT cana-844 157 8 1074 1074 NUM cana-844 157 9 - - PUNCT cana-844 157 10 133x 133x NUM cana-844 157 11 vol vol NOUN cana-844 157 12 31 31 NUM cana-844 157 13 no no NOUN cana-844 157 14 . . PUNCT cana-844 158 1 4s 4s NUM cana-844 158 2 ( ( PUNCT cana-844 158 3 2024 2024 NUM cana-844 158 4 ) ) PUNCT cana-844 158 5 238 238 NUM cana-844 158 6 https://internationalpubls.com https://internationalpubls.com X cana-844 158 7 fig fig NOUN cana-844 158 8 3 3 NUM cana-844 158 9 : : PUNCT cana-844 158 10 architecture architecture NOUN cana-844 158 11 of of ADP cana-844 158 12 vgg19 vgg19 PROPN cana-844 158 13 the the DET cana-844 158 14 vgg19 vgg19 NOUN cana-844 158 15 model model NOUN cana-844 158 16 is be AUX cana-844 158 17 recognized recognize VERB cana-844 158 18 for for ADP cana-844 158 19 its its PRON cana-844 158 20 simple simple ADJ cana-844 158 21 and and CCONJ cana-844 158 22 consistent consistent ADJ cana-844 158 23 design design NOUN cana-844 158 24 , , PUNCT cana-844 158 25 which which PRON cana-844 158 26 makes make VERB cana-844 158 27 it it PRON cana-844 158 28 straightforward straightforward ADJ cana-844 158 29 to to PART cana-844 158 30 comprehend comprehend VERB cana-844 158 31 and and CCONJ cana-844 158 32 adjust adjust VERB cana-844 158 33 . . PUNCT cana-844 159 1 it it PRON cana-844 159 2 is be AUX cana-844 159 3 commonly commonly ADV cana-844 159 4 employed employ VERB cana-844 159 5 as as ADP cana-844 159 6 a a DET cana-844 159 7 feature feature NOUN cana-844 159 8 extractor extractor NOUN cana-844 159 9 and and CCONJ cana-844 159 10 in in ADP cana-844 159 11 transfer transfer NOUN cana-844 159 12 learning learn VERB cana-844 159 13 assignments assignment NOUN cana-844 159 14 for for ADP cana-844 159 15 different different ADJ cana-844 159 16 computer computer NOUN cana-844 159 17 vision vision NOUN cana-844 159 18 task task NOUN cana-844 159 19 . . PUNCT cana-844 160 1 3.3.2 3.3.2 NUM cana-844 160 2 resnet50 resnet50 NOUN cana-844 160 3 when when SCONJ cana-844 160 4 facing face VERB cana-844 160 5 challenges challenge NOUN cana-844 160 6 like like ADP cana-844 160 7 disappearing disappear VERB cana-844 160 8 or or CCONJ cana-844 160 9 exploding explode VERB cana-844 160 10 gradients gradient NOUN cana-844 160 11 during during ADP cana-844 160 12 training training NOUN cana-844 160 13 , , PUNCT cana-844 160 14 he he PRON cana-844 160 15 et et PROPN cana-844 160 16 al al PROPN cana-844 160 17 . . PROPN cana-844 160 18 introduced introduce VERB cana-844 160 19 resnet resnet PROPN cana-844 160 20 , , PUNCT cana-844 160 21 a a DET cana-844 160 22 new new ADJ cana-844 160 23 residual residual ADJ cana-844 160 24 network network NOUN cana-844 160 25 [ [ X cana-844 160 26 18 18 NUM cana-844 160 27 ] ] PUNCT cana-844 160 28 . . PUNCT cana-844 161 1 fig fig NOUN cana-844 161 2 4 4 NUM cana-844 161 3 illustrates illustrate VERB cana-844 161 4 the the DET cana-844 161 5 architecture architecture NOUN cana-844 161 6 of of ADP cana-844 161 7 resnet50 resnet50 NOUN cana-844 161 8 . . PUNCT cana-844 162 1 fig fig NOUN cana-844 162 2 4 4 NUM cana-844 162 3 : : PUNCT cana-844 162 4 architecture architecture NOUN cana-844 162 5 of of ADP cana-844 162 6 resnet50 resnet50 NOUN cana-844 162 7 resnet resnet PROPN cana-844 162 8 's 's PART cana-844 162 9 core core ADJ cana-844 162 10 idea idea NOUN cana-844 162 11 is be AUX cana-844 162 12 to to PART cana-844 162 13 incorporate incorporate VERB cana-844 162 14 an an DET cana-844 162 15 identity identity NOUN cana-844 162 16 shortcut shortcut NOUN cana-844 162 17 connection connection NOUN cana-844 162 18 that that PRON cana-844 162 19 skips skip VERB cana-844 162 20 certain certain ADJ cana-844 162 21 layers layer NOUN cana-844 162 22 , , PUNCT cana-844 162 23 using use VERB cana-844 162 24 skip skip ADJ cana-844 162 25 connections connection NOUN cana-844 162 26 to to PART cana-844 162 27 link link VERB cana-844 162 28 specific specific ADJ cana-844 162 29 layers layer NOUN cana-844 162 30 and and CCONJ cana-844 162 31 facilitate facilitate NOUN cana-844 162 32 learning learning NOUN cana-844 162 33 of of ADP cana-844 162 34 residual residual ADJ cana-844 162 35 mappings mapping NOUN cana-844 162 36 . . PUNCT cana-844 163 1 it it PRON cana-844 163 2 makes make VERB cana-844 163 3 use use NOUN cana-844 163 4 of of ADP cana-844 163 5 a a DET cana-844 163 6 method method NOUN cana-844 163 7 called call VERB cana-844 163 8 skip skip ADJ cana-844 163 9 connections connection NOUN cana-844 163 10 , , PUNCT cana-844 163 11 which which PRON cana-844 163 12 connects connect VERB cana-844 163 13 skip skip ADJ cana-844 163 14 connections connection NOUN cana-844 163 15 between between ADP cana-844 163 16 the the DET cana-844 163 17 architectures architecture NOUN cana-844 163 18 on on ADP cana-844 163 19 up up ADP cana-844 163 20 to to PART cana-844 163 21 three three NUM cana-844 163 22 layers layer NOUN cana-844 163 23 that that PRON cana-844 163 24 incorporate incorporate VERB cana-844 163 25 batch batch NOUN cana-844 163 26 normalisation normalisation NOUN cana-844 163 27 and and CCONJ cana-844 163 28 relu relu NOUN cana-844 164 1 [ [ X cana-844 164 2 19 19 NUM cana-844 164 3 ] ] PUNCT cana-844 164 4 . . PUNCT cana-844 165 1 this this DET cana-844 165 2 approach approach NOUN cana-844 165 3 allows allow VERB cana-844 165 4 the the DET cana-844 165 5 network network NOUN cana-844 165 6 to to PART cana-844 165 7 focus focus VERB cana-844 165 8 on on ADP cana-844 165 9 matching match VERB cana-844 165 10 the the DET cana-844 165 11 residual residual ADJ cana-844 165 12 mapping mapping NOUN cana-844 165 13 instead instead ADV cana-844 165 14 of of ADP cana-844 165 15 learning learn VERB cana-844 165 16 the the DET cana-844 165 17 underlying underlie VERB cana-844 165 18 one one NUM cana-844 165 19 . . PUNCT cana-844 166 1 in in ADP cana-844 166 2 simpler simple ADJ cana-844 166 3 terms term NOUN cana-844 166 4 , , PUNCT cana-844 166 5 by by ADP cana-844 166 6 considering consider VERB cana-844 166 7 h(x h(x PROPN cana-844 166 8 ) ) PUNCT cana-844 166 9 as as ADP cana-844 166 10 the the DET cana-844 166 11 target target NOUN cana-844 166 12 mapping mapping NOUN cana-844 166 13 for for ADP cana-844 166 14 stacked stack VERB cana-844 166 15 layers layer NOUN cana-844 166 16 starting start VERB cana-844 166 17 with with ADP cana-844 166 18 input input NOUN cana-844 166 19 " " PUNCT cana-844 166 20 x x NOUN cana-844 166 21 , , PUNCT cana-844 166 22 " " PUNCT cana-844 166 23 resnet resnet NOUN cana-844 166 24 aims aim VERB cana-844 166 25 to to PART cana-844 166 26 approximate approximate VERB cana-844 166 27 the the DET cana-844 166 28 residual residual ADJ cana-844 166 29 function function NOUN cana-844 166 30 f(x f(x PROPN cana-844 166 31 ) ) PUNCT cana-844 167 1 = = SYM cana-844 167 2 h(x h(x PROPN cana-844 167 3 ) ) PUNCT cana-844 167 4 x x NOUN cana-844 167 5 , , PUNCT cana-844 167 6 leading lead VERB cana-844 167 7 to to ADP cana-844 167 8 the the DET cana-844 167 9 final final ADJ cana-844 167 10 function function NOUN cana-844 167 11 f(x f(x PROPN cana-844 167 12 ) ) PUNCT cana-844 168 1 + + CCONJ cana-844 168 2 x. x. NOUN cana-844 168 3 resnet-50 resnet-50 PROPN cana-844 168 4 is be AUX cana-844 168 5 a a DET cana-844 168 6 deep deep ADJ cana-844 168 7 neural neural ADJ cana-844 168 8 network network NOUN cana-844 168 9 consisting consist VERB cana-844 168 10 of of ADP cana-844 168 11 50 50 NUM cana-844 168 12 layers layer NOUN cana-844 168 13 , , PUNCT cana-844 168 14 allowing allow VERB cana-844 168 15 it it PRON cana-844 168 16 to to PART cana-844 168 17 learn learn VERB cana-844 168 18 intricate intricate ADJ cana-844 168 19 features feature NOUN cana-844 168 20 from from ADP cana-844 168 21 input input NOUN cana-844 168 22 data datum NOUN cana-844 168 23 for for ADP cana-844 168 24 improved improved ADJ cana-844 168 25 performance performance NOUN cana-844 168 26 in in ADP cana-844 168 27 computer computer NOUN cana-844 168 28 vision vision NOUN cana-844 168 29 tasks task NOUN cana-844 168 30 . . PUNCT cana-844 169 1 the the DET cana-844 169 2 inclusion inclusion NOUN cana-844 169 3 of of ADP cana-844 169 4 residual residual ADJ cana-844 169 5 connections connection NOUN cana-844 169 6 in in ADP cana-844 169 7 resnet-50 resnet-50 NOUN cana-844 169 8 addresses address NOUN cana-844 169 9 the the DET cana-844 169 10 vanishing vanish VERB cana-844 169 11 gradient gradient NOUN cana-844 169 12 issue issue NOUN cana-844 169 13 , , PUNCT cana-844 169 14 resulting result VERB cana-844 169 15 in in ADP cana-844 169 16 higher high ADJ cana-844 169 17 accuracy accuracy NOUN cana-844 169 18 for for ADP cana-844 169 19 image image NOUN cana-844 169 20 classification classification NOUN cana-844 169 21 tasks task NOUN cana-844 169 22 compared compare VERB cana-844 169 23 to to ADP cana-844 169 24 earlier early ADJ cana-844 169 25 cnn cnn PROPN cana-844 169 26 models model NOUN cana-844 169 27 on on ADP cana-844 169 28 standard standard ADJ cana-844 169 29 datasets dataset NOUN cana-844 169 30 . . PUNCT cana-844 170 1 communications communication NOUN cana-844 170 2 on on ADP cana-844 170 3 applied apply VERB cana-844 170 4 nonlinear nonlinear ADJ cana-844 170 5 analysis analysis NOUN cana-844 170 6 issn issn NOUN cana-844 170 7 : : PUNCT cana-844 170 8 1074 1074 NUM cana-844 170 9 - - PUNCT cana-844 170 10 133x 133x NUM cana-844 170 11 vol vol NOUN cana-844 170 12 31 31 NUM cana-844 170 13 no no NOUN cana-844 170 14 . . PUNCT cana-844 171 1 4s 4s NUM cana-844 171 2 ( ( PUNCT cana-844 171 3 2024 2024 NUM cana-844 171 4 ) ) PUNCT cana-844 171 5 239 239 NUM cana-844 171 6 https://internationalpubls.com https://internationalpubls.com SYM cana-844 171 7 3.4 3.4 NUM cana-844 171 8 feature feature NOUN cana-844 171 9 selection selection NOUN cana-844 171 10 feature feature NOUN cana-844 171 11 selection selection NOUN cana-844 171 12 is be AUX cana-844 171 13 a a DET cana-844 171 14 process process NOUN cana-844 171 15 of of ADP cana-844 171 16 identifying identify VERB cana-844 171 17 and and CCONJ cana-844 171 18 selecting select VERB cana-844 171 19 the the DET cana-844 171 20 most most ADV cana-844 171 21 important important ADJ cana-844 171 22 features feature NOUN cana-844 171 23 in in ADP cana-844 171 24 image image NOUN cana-844 171 25 datasets dataset NOUN cana-844 171 26 that that PRON cana-844 171 27 helps help VERB cana-844 171 28 to to PART cana-844 171 29 enhance enhance VERB cana-844 171 30 the the DET cana-844 171 31 performance performance NOUN cana-844 171 32 of of ADP cana-844 171 33 machine machine NOUN cana-844 171 34 learning learning NOUN cana-844 171 35 models model NOUN cana-844 171 36 . . PUNCT cana-844 172 1 utilizing utilize VERB cana-844 172 2 random random ADJ cana-844 172 3 forest forest NOUN cana-844 172 4 for for ADP cana-844 172 5 feature feature NOUN cana-844 172 6 selection selection NOUN cana-844 172 7 falls fall VERB cana-844 172 8 within within ADP cana-844 172 9 the the DET cana-844 172 10 embedded embed VERB cana-844 172 11 methods method NOUN cana-844 172 12 category category NOUN cana-844 172 13 , , PUNCT cana-844 172 14 which which PRON cana-844 172 15 merges merge VERB cana-844 172 16 the the DET cana-844 172 17 characteristics characteristic NOUN cana-844 172 18 of of ADP cana-844 172 19 filter filter NOUN cana-844 172 20 and and CCONJ cana-844 172 21 wrapper wrapper NOUN cana-844 172 22 methods method NOUN cana-844 172 23 . . PUNCT cana-844 173 1 a a DET cana-844 173 2 random random ADJ cana-844 173 3 forest forest NOUN cana-844 173 4 comprises comprise VERB cana-844 173 5 4 4 NUM cana-844 173 6 to to PART cana-844 173 7 1200 1200 NUM cana-844 173 8 decision decision NOUN cana-844 173 9 trees tree NOUN cana-844 173 10 , , PUNCT cana-844 173 11 with with SCONJ cana-844 173 12 each each DET cana-844 173 13 tree tree NOUN cana-844 173 14 constructed construct VERB cana-844 173 15 using use VERB cana-844 173 16 a a DET cana-844 173 17 random random ADJ cana-844 173 18 selection selection NOUN cana-844 173 19 of of ADP cana-844 173 20 observations observation NOUN cana-844 173 21 and and CCONJ cana-844 173 22 features feature NOUN cana-844 173 23 from from ADP cana-844 173 24 the the DET cana-844 173 25 dataset dataset NOUN cana-844 173 26 . . PUNCT cana-844 174 1 not not PART cana-844 174 2 all all DET cana-844 174 3 trees tree NOUN cana-844 174 4 see see VERB cana-844 174 5 the the DET cana-844 174 6 same same ADJ cana-844 174 7 features feature NOUN cana-844 174 8 or or CCONJ cana-844 174 9 observations observation NOUN cana-844 174 10 , , PUNCT cana-844 174 11 ensuring ensure VERB cana-844 174 12 that that SCONJ cana-844 174 13 the the DET cana-844 174 14 trees tree NOUN cana-844 174 15 are be AUX cana-844 174 16 not not PART cana-844 174 17 correlated correlate VERB cana-844 174 18 and and CCONJ cana-844 174 19 less less ADV cana-844 174 20 likely likely ADJ cana-844 174 21 to to PART cana-844 174 22 overfit overfit VERB cana-844 174 23 . . PUNCT cana-844 175 1 each each DET cana-844 175 2 tree tree NOUN cana-844 175 3 consists consist VERB cana-844 175 4 of of ADP cana-844 175 5 a a DET cana-844 175 6 series series NOUN cana-844 175 7 of of ADP cana-844 175 8 yes yes ADV cana-844 175 9 - - PUNCT cana-844 175 10 or or CCONJ cana-844 175 11 - - PUNCT cana-844 175 12 no no PRON cana-844 175 13 questions question NOUN cana-844 175 14 based base VERB cana-844 175 15 on on ADP cana-844 175 16 one one NUM cana-844 175 17 or or CCONJ cana-844 175 18 more more ADJ cana-844 175 19 features feature NOUN cana-844 175 20 . . PUNCT cana-844 176 1 at at ADP cana-844 176 2 each each DET cana-844 176 3 node node NOUN cana-844 176 4 ( ( PUNCT cana-844 176 5 question question NOUN cana-844 176 6 ) ) PUNCT cana-844 176 7 , , PUNCT cana-844 176 8 the the DET cana-844 176 9 tree tree NOUN cana-844 176 10 splits split VERB cana-844 176 11 the the DET cana-844 176 12 dataset dataset NOUN cana-844 176 13 into into ADP cana-844 176 14 two two NUM cana-844 176 15 groups group NOUN cana-844 176 16 , , PUNCT cana-844 176 17 each each PRON cana-844 176 18 containing contain VERB cana-844 176 19 observations observation NOUN cana-844 176 20 that that PRON cana-844 176 21 are be AUX cana-844 176 22 more more ADV cana-844 176 23 similar similar ADJ cana-844 176 24 to to ADP cana-844 176 25 each each DET cana-844 176 26 other other ADJ cana-844 176 27 and and CCONJ cana-844 176 28 different different ADJ cana-844 176 29 from from ADP cana-844 176 30 those those PRON cana-844 176 31 in in ADP cana-844 176 32 the the DET cana-844 176 33 other other ADJ cana-844 176 34 group group NOUN cana-844 176 35 . . PUNCT cana-844 177 1 therefore therefore ADV cana-844 177 2 , , PUNCT cana-844 177 3 the the DET cana-844 177 4 significance significance NOUN cana-844 177 5 of of ADP cana-844 177 6 each each DET cana-844 177 7 feature feature NOUN cana-844 177 8 is be AUX cana-844 177 9 determined determine VERB cana-844 177 10 by by ADP cana-844 177 11 the the DET cana-844 177 12 level level NOUN cana-844 177 13 of of ADP cana-844 177 14 " " PUNCT cana-844 177 15 purity purity NOUN cana-844 177 16 " " PUNCT cana-844 177 17 in in ADP cana-844 177 18 each each DET cana-844 177 19 group group NOUN cana-844 177 20 [ [ X cana-844 177 21 20 20 NUM cana-844 177 22 ] ] PUNCT cana-844 177 23 . . PUNCT cana-844 178 1 random random ADJ cana-844 178 2 forests forest NOUN cana-844 178 3 typically typically ADV cana-844 178 4 rely rely VERB cana-844 178 5 on on ADP cana-844 178 6 gini gini PROPN cana-844 178 7 index index PROPN cana-844 178 8 to to PART cana-844 178 9 assess assess VERB cana-844 178 10 the the DET cana-844 178 11 importance importance NOUN cana-844 178 12 of of ADP cana-844 178 13 features feature NOUN cana-844 178 14 which which PRON cana-844 178 15 is be AUX cana-844 178 16 defined define VERB cana-844 178 17 in in ADP cana-844 178 18 equation equation NOUN cana-844 178 19 1 1 NUM cana-844 178 20 . . PUNCT cana-844 179 1 gini gini PROPN cana-844 179 2 ( ( PUNCT cana-844 179 3 t t PROPN cana-844 179 4 ) ) PUNCT cana-844 179 5 = = SYM cana-844 179 6 1-βˆ‘ 1-βˆ‘ PROPN cana-844 179 7 𝑝(𝑖 𝑝(𝑖 PROPN cana-844 179 8 𝑑⁄ 𝑑⁄ NUM cana-844 179 9 ) ) PUNCT cana-844 179 10 2π‘˜ 2π‘˜ NUM cana-844 179 11 𝑖=1 𝑖=1 PUNCT cana-844 179 12 ( ( PUNCT cana-844 179 13 1 1 X cana-844 179 14 ) ) PUNCT cana-844 179 15 this this DET cana-844 179 16 metric metric NOUN cana-844 179 17 is be AUX cana-844 179 18 determined determine VERB cana-844 179 19 by by ADP cana-844 179 20 how how SCONJ cana-844 179 21 effectively effectively ADV cana-844 179 22 each each DET cana-844 179 23 feature feature NOUN cana-844 179 24 reduces reduce VERB cana-844 179 25 impurity impurity NOUN cana-844 179 26 throughout throughout ADP cana-844 179 27 all all DET cana-844 179 28 decision decision NOUN cana-844 179 29 trees tree NOUN cana-844 179 30 within within ADP cana-844 179 31 the the DET cana-844 179 32 forest forest NOUN cana-844 179 33 . . PUNCT cana-844 180 1 gini gini NOUN cana-844 180 2 importance importance NOUN cana-844 180 3 values value NOUN cana-844 180 4 range range VERB cana-844 180 5 from from ADP cana-844 180 6 0 0 NUM cana-844 180 7 to to ADP cana-844 180 8 0.5 0.5 NUM cana-844 180 9 , , PUNCT cana-844 180 10 with with ADP cana-844 180 11 0 0 NUM cana-844 180 12 indicating indicate VERB cana-844 180 13 ideal ideal ADJ cana-844 180 14 purity purity NOUN cana-844 180 15 ( ( PUNCT cana-844 180 16 all all DET cana-844 180 17 elements element NOUN cana-844 180 18 assigned assign VERB cana-844 180 19 to to ADP cana-844 180 20 the the DET cana-844 180 21 same same ADJ cana-844 180 22 class class NOUN cana-844 180 23 ) ) PUNCT cana-844 180 24 and and CCONJ cana-844 180 25 0.5 0.5 NUM cana-844 180 26 indicating indicate VERB cana-844 180 27 maximum maximum ADJ cana-844 180 28 impurity impurity NOUN cana-844 180 29 ( ( PUNCT cana-844 180 30 labels label NOUN cana-844 180 31 evenly evenly ADV cana-844 180 32 distributed distribute VERB cana-844 180 33 across across ADP cana-844 180 34 all all DET cana-844 180 35 classes).now classes).now PROPN cana-844 180 36 on on ADP cana-844 180 37 the the DET cana-844 180 38 basis basis NOUN cana-844 180 39 of of ADP cana-844 180 40 feature feature NOUN cana-844 180 41 importance importance NOUN cana-844 180 42 score score NOUN cana-844 180 43 , , PUNCT cana-844 180 44 select select VERB cana-844 180 45 the the DET cana-844 180 46 features feature NOUN cana-844 180 47 that that PRON cana-844 180 48 are be AUX cana-844 180 49 present present ADJ cana-844 180 50 at at ADP cana-844 180 51 top top NOUN cana-844 180 52 of of ADP cana-844 180 53 the the DET cana-844 180 54 tree tree NOUN cana-844 180 55 as as SCONJ cana-844 180 56 it it PRON cana-844 180 57 provides provide VERB cana-844 180 58 more more ADJ cana-844 180 59 information information NOUN cana-844 180 60 . . PUNCT cana-844 181 1 this this DET cana-844 181 2 technique technique NOUN cana-844 181 3 is be AUX cana-844 181 4 highly highly ADV cana-844 181 5 accurate accurate ADJ cana-844 181 6 and and CCONJ cana-844 181 7 faster fast ADV cana-844 181 8 as as SCONJ cana-844 181 9 compared compare VERB cana-844 181 10 to to ADP cana-844 181 11 other other ADJ cana-844 181 12 techniques technique NOUN cana-844 181 13 . . PUNCT cana-844 182 1 3.5 3.5 NUM cana-844 182 2 feature feature NOUN cana-844 182 3 fusion fusion NOUN cana-844 182 4 and and CCONJ cana-844 182 5 classification classification NOUN cana-844 182 6 finally finally ADV cana-844 182 7 the the DET cana-844 182 8 features feature NOUN cana-844 182 9 that that PRON cana-844 182 10 are be AUX cana-844 182 11 selected select VERB cana-844 182 12 using use VERB cana-844 182 13 feature feature NOUN cana-844 182 14 selection selection NOUN cana-844 182 15 technique technique NOUN cana-844 182 16 from from ADP cana-844 182 17 the the DET cana-844 182 18 mri mri NOUN cana-844 182 19 scans scan NOUN cana-844 182 20 are be AUX cana-844 182 21 fused fuse VERB cana-844 182 22 with with ADP cana-844 182 23 genomic genomic ADJ cana-844 182 24 feature feature NOUN cana-844 182 25 i.e. i.e. X cana-844 182 26 mgmt mgmt PROPN cana-844 182 27 promoter promoter NOUN cana-844 182 28 methylation methylation NOUN cana-844 182 29 into into ADP cana-844 182 30 a a DET cana-844 182 31 single single ADJ cana-844 182 32 file file NOUN cana-844 182 33 . . PUNCT cana-844 183 1 the the DET cana-844 183 2 fused fuse VERB cana-844 183 3 features feature NOUN cana-844 183 4 are be AUX cana-844 183 5 passed pass VERB cana-844 183 6 to to ADP cana-844 183 7 machine machine NOUN cana-844 183 8 learning learn VERB cana-844 183 9 algorithms algorithm NOUN cana-844 183 10 for for ADP cana-844 183 11 the the DET cana-844 183 12 final final ADJ cana-844 183 13 classification classification NOUN cana-844 183 14 . . PUNCT cana-844 184 1 3.5.1 3.5.1 NUM cana-844 185 1 k k ADJ cana-844 185 2 - - PUNCT cana-844 185 3 nearest near ADJ cana-844 185 4 neighbour neighbour NOUN cana-844 185 5 the the DET cana-844 185 6 popular popular ADJ cana-844 185 7 knn knn PROPN cana-844 185 8 algorithm algorithm PROPN cana-844 185 9 is be AUX cana-844 185 10 a a DET cana-844 185 11 supervised supervised ADJ cana-844 185 12 machine machine NOUN cana-844 185 13 learning learning NOUN cana-844 185 14 method method NOUN cana-844 185 15 mainly mainly ADV cana-844 185 16 applied apply VERB cana-844 185 17 for for ADP cana-844 185 18 classification classification NOUN cana-844 185 19 tasks task NOUN cana-844 185 20 [ [ X cana-844 185 21 21 21 NUM cana-844 185 22 ] ] PUNCT cana-844 185 23 . . PUNCT cana-844 186 1 the the DET cana-844 186 2 algorithm algorithm NOUN cana-844 186 3 involves involve VERB cana-844 186 4 a a DET cana-844 186 5 variable variable NOUN cana-844 186 6 called call VERB cana-844 186 7 k k PROPN cana-844 186 8 , , PUNCT cana-844 186 9 which which PRON cana-844 186 10 indicates indicate VERB cana-844 186 11 the the DET cana-844 186 12 number number NOUN cana-844 186 13 of of ADP cana-844 186 14 ' ' PUNCT cana-844 186 15 nearest near ADJ cana-844 186 16 neighbors neighbor NOUN cana-844 186 17 ' ' PART cana-844 186 18 . . PUNCT cana-844 187 1 in in ADP cana-844 187 2 operation operation NOUN cana-844 187 3 , , PUNCT cana-844 187 4 knn knn PROPN cana-844 187 5 locates locate VERB cana-844 187 6 the the DET cana-844 187 7 closest close ADJ cana-844 187 8 data datum NOUN cana-844 187 9 point(s point(s NOUN cana-844 187 10 ) ) PUNCT cana-844 187 11 or or CCONJ cana-844 187 12 neighbor(s neighbor(s NOUN cana-844 187 13 ) ) PUNCT cana-844 187 14 from from ADP cana-844 187 15 a a DET cana-844 187 16 training training NOUN cana-844 187 17 set set NOUN cana-844 187 18 for for ADP cana-844 187 19 a a DET cana-844 187 20 given give VERB cana-844 187 21 query query NOUN cana-844 187 22 . . PUNCT cana-844 188 1 it it PRON cana-844 188 2 utilizes utilize VERB cana-844 188 3 euclidean euclidean ADJ cana-844 188 4 distance distance NOUN cana-844 188 5 to to PART cana-844 188 6 compute compute VERB cana-844 188 7 the the DET cana-844 188 8 distance distance NOUN cana-844 188 9 between between ADP cana-844 188 10 data datum NOUN cana-844 188 11 points point NOUN cana-844 188 12 , , PUNCT cana-844 188 13 as as SCONJ cana-844 188 14 shown show VERB cana-844 188 15 in in ADP cana-844 188 16 the the DET cana-844 188 17 formula formula NOUN cana-844 188 18 below below ADP cana-844 188 19 in in ADP cana-844 188 20 equation equation NOUN cana-844 188 21 2 2 NUM cana-844 189 1 [ [ X cana-844 189 2 22 22 NUM cana-844 189 3 ] ] X cana-844 189 4 : : PUNCT cana-844 190 1 d(y d(y NOUN cana-844 190 2 , , PUNCT cana-844 190 3 z z NOUN cana-844 190 4 ) ) PUNCT cana-844 190 5 = = PRON cana-844 190 6 βˆšβˆ‘ βˆšβˆ‘ X cana-844 190 7 ( ( PUNCT cana-844 190 8 𝑦𝑖 𝑦𝑖 PROPN cana-844 190 9 βˆ’ βˆ’ PROPN cana-844 190 10 𝑧𝑖)2 𝑧𝑖)2 PROPN cana-844 190 11 𝑛 𝑛 VERB cana-844 190 12 𝑖 𝑖 X cana-844 190 13 ( ( PUNCT cana-844 190 14 2 2 NUM cana-844 190 15 ) ) PUNCT cana-844 190 16 nearest near ADJ cana-844 190 17 data datum NOUN cana-844 190 18 points point NOUN cana-844 190 19 are be AUX cana-844 190 20 identified identify VERB cana-844 190 21 based base VERB cana-844 190 22 on on ADP cana-844 190 23 their their PRON cana-844 190 24 proximity proximity NOUN cana-844 190 25 to to ADP cana-844 190 26 the the DET cana-844 190 27 query query NOUN cana-844 190 28 point point NOUN cana-844 190 29 . . PUNCT cana-844 191 1 once once SCONJ cana-844 191 2 the the DET cana-844 191 3 k k PROPN cana-844 191 4 nearest near ADJ cana-844 191 5 data datum NOUN cana-844 191 6 points point NOUN cana-844 191 7 are be AUX cana-844 191 8 determined determine VERB cana-844 191 9 , , PUNCT cana-844 191 10 a a DET cana-844 191 11 majority majority NOUN cana-844 191 12 voting voting NOUN cana-844 191 13 rule rule NOUN cana-844 191 14 is be AUX cana-844 191 15 applied apply VERB cana-844 191 16 to to PART cana-844 191 17 determine determine VERB cana-844 191 18 the the DET cana-844 191 19 most most ADV cana-844 191 20 frequently frequently ADV cana-844 191 21 occurring occur VERB cana-844 191 22 class class NOUN cana-844 191 23 . . PUNCT cana-844 192 1 the the DET cana-844 192 2 class class NOUN cana-844 192 3 with with ADP cana-844 192 4 the the DET cana-844 192 5 highest high ADJ cana-844 192 6 frequency frequency NOUN cana-844 192 7 is be AUX cana-844 192 8 designated designate VERB cana-844 192 9 as as ADP cana-844 192 10 the the DET cana-844 192 11 final final ADJ cana-844 192 12 classification classification NOUN cana-844 192 13 for for ADP cana-844 192 14 the the DET cana-844 192 15 query query NOUN cana-844 192 16 . . PUNCT cana-844 193 1 k k X cana-844 193 2 - - PUNCT cana-844 193 3 nn nn PROPN cana-844 193 4 is be AUX cana-844 193 5 simple simple ADJ cana-844 193 6 to to ADP cana-844 193 7 grasp grasp NOUN cana-844 193 8 and and CCONJ cana-844 193 9 use use VERB cana-844 193 10 , , PUNCT cana-844 193 11 making make VERB cana-844 193 12 it it PRON cana-844 193 13 suitable suitable ADJ cana-844 193 14 even even ADV cana-844 193 15 for for ADP cana-844 193 16 those those PRON cana-844 193 17 unfamiliar unfamiliar ADJ cana-844 193 18 with with ADP cana-844 193 19 machine machine NOUN cana-844 193 20 learning learning NOUN cana-844 193 21 . . PUNCT cana-844 194 1 it it PRON cana-844 194 2 can can AUX cana-844 194 3 manage manage VERB cana-844 194 4 data datum NOUN cana-844 194 5 with with ADP cana-844 194 6 irregular irregular ADJ cana-844 194 7 boundaries boundary NOUN cana-844 194 8 or or CCONJ cana-844 194 9 non non ADJ cana-844 194 10 - - ADJ cana-844 194 11 linear linear ADJ cana-844 194 12 connections connection NOUN cana-844 194 13 between between ADP cana-844 194 14 features feature NOUN cana-844 194 15 and and CCONJ cana-844 194 16 labels label NOUN cana-844 194 17 . . PUNCT cana-844 195 1 communications communication NOUN cana-844 195 2 on on ADP cana-844 195 3 applied apply VERB cana-844 195 4 nonlinear nonlinear ADJ cana-844 195 5 analysis analysis NOUN cana-844 195 6 issn issn NOUN cana-844 195 7 : : PUNCT cana-844 195 8 1074 1074 NUM cana-844 195 9 - - PUNCT cana-844 195 10 133x 133x NUM cana-844 195 11 vol vol NOUN cana-844 195 12 31 31 NUM cana-844 195 13 no no NOUN cana-844 195 14 . . PUNCT cana-844 196 1 4s 4s NUM cana-844 196 2 ( ( PUNCT cana-844 196 3 2024 2024 NUM cana-844 196 4 ) ) PUNCT cana-844 196 5 240 240 NUM cana-844 196 6 https://internationalpubls.com https://internationalpubls.com X cana-844 196 7 3.5.2 3.5.2 NUM cana-844 196 8 naive naive ADJ cana-844 196 9 bayes baye NOUN cana-844 196 10 the the DET cana-844 196 11 naive naive ADJ cana-844 196 12 bayes bayes NOUN cana-844 196 13 method method NOUN cana-844 196 14 simplifies simplify VERB cana-844 196 15 the the DET cana-844 196 16 calculation calculation NOUN cana-844 196 17 of of ADP cana-844 196 18 conditional conditional ADJ cana-844 196 19 probabilities probability NOUN cana-844 196 20 by by ADP cana-844 196 21 assuming assume VERB cana-844 196 22 that that SCONJ cana-844 196 23 the the DET cana-844 196 24 features feature NOUN cana-844 196 25 are be AUX cana-844 196 26 independent independent ADJ cana-844 196 27 given give VERB cana-844 196 28 the the DET cana-844 196 29 class class NOUN cana-844 196 30 . . PUNCT cana-844 197 1 naive naive ADJ cana-844 197 2 bayes bayes PROPN cana-844 197 3 classifiers classifier NOUN cana-844 197 4 are be AUX cana-844 197 5 created create VERB cana-844 197 6 using use VERB cana-844 197 7 bayes baye NOUN cana-844 197 8 ' ' PART cana-844 197 9 theorem theorem NOUN cana-844 197 10 , , PUNCT cana-844 197 11 consisting consist VERB cana-844 197 12 of of ADP cana-844 197 13 algorithms algorithm NOUN cana-844 197 14 that that PRON cana-844 197 15 operate operate VERB cana-844 197 16 on on ADP cana-844 197 17 the the DET cana-844 197 18 principle principle NOUN cana-844 197 19 that that SCONJ cana-844 197 20 each each DET cana-844 197 21 pair pair NOUN cana-844 197 22 of of ADP cana-844 197 23 features feature NOUN cana-844 197 24 to to PART cana-844 197 25 be be AUX cana-844 197 26 categorized categorize VERB cana-844 197 27 is be AUX cana-844 197 28 independent independent ADJ cana-844 197 29 [ [ X cana-844 197 30 23 23 NUM cana-844 197 31 ] ] PUNCT cana-844 197 32 . . PUNCT cana-844 198 1 the the DET cana-844 198 2 naive naive ADJ cana-844 198 3 bayes bayes NOUN cana-844 198 4 model model NOUN cana-844 198 5 is be AUX cana-844 198 6 suitable suitable ADJ cana-844 198 7 for for ADP cana-844 198 8 handling handle VERB cana-844 198 9 very very ADV cana-844 198 10 large large ADJ cana-844 198 11 datasets dataset NOUN cana-844 198 12 and and CCONJ cana-844 198 13 conducting conduct VERB cana-844 198 14 additional additional ADJ cana-844 198 15 analysis analysis NOUN cana-844 198 16 . . PUNCT cana-844 199 1 it it PRON cana-844 199 2 is be AUX cana-844 199 3 a a DET cana-844 199 4 straightforward straightforward ADJ cana-844 199 5 yet yet CCONJ cana-844 199 6 effective effective ADJ cana-844 199 7 classification classification NOUN cana-844 199 8 approach approach NOUN cana-844 199 9 that that PRON cana-844 199 10 delivers deliver VERB cana-844 199 11 strong strong ADJ cana-844 199 12 performance performance NOUN cana-844 199 13 , , PUNCT cana-844 199 14 even even ADV cana-844 199 15 in in ADP cana-844 199 16 complex complex ADJ cana-844 199 17 situations situation NOUN cana-844 199 18 [ [ X cana-844 199 19 24 24 NUM cana-844 199 20 ] ] PUNCT cana-844 199 21 . . PUNCT cana-844 200 1 utilize utilize VERB cana-844 200 2 bayes bayes PROPN cana-844 200 3 ' ' PART cana-844 200 4 theorem theorem NOUN cana-844 200 5 to to PART cana-844 200 6 compute compute VERB cana-844 200 7 the the DET cana-844 200 8 posterior posterior ADJ cana-844 200 9 probability probability NOUN cana-844 200 10 with with ADP cana-844 200 11 the the DET cana-844 200 12 provided provide VERB cana-844 200 13 equation equation NOUN cana-844 200 14 : : PUNCT cana-844 200 15 𝑃 𝑃 PROPN cana-844 200 16 ( ( PUNCT cana-844 200 17 π‘Œ π‘Œ PROPN cana-844 200 18 𝑋⁄ 𝑋⁄ PROPN cana-844 200 19 ) ) PUNCT cana-844 201 1 = = SYM cana-844 201 2 ⁑𝑃(𝑋 ⁑𝑃(𝑋 PROPN cana-844 201 3 π‘Œβ„ π‘Œβ„ PROPN cana-844 201 4 ) ) PUNCT cana-844 202 1 ⁑p(y ⁑p(y X cana-844 202 2 ) ) PUNCT cana-844 202 3 𝑃(𝑋 𝑃(𝑋 PROPN cana-844 202 4 ) ) PUNCT cana-844 202 5 ( ( PUNCT cana-844 202 6 3 3 X cana-844 202 7 ) ) PUNCT cana-844 202 8 p(x p(x PROPN cana-844 202 9 / / SYM cana-844 202 10 y y NOUN cana-844 202 11 ) ) PUNCT cana-844 202 12 represents represent VERB cana-844 202 13 the the DET cana-844 202 14 posterior posterior ADJ cana-844 202 15 probability probability NOUN cana-844 202 16 of of ADP cana-844 202 17 a a DET cana-844 202 18 class class NOUN cana-844 202 19 , , PUNCT cana-844 202 20 while while SCONJ cana-844 202 21 p(x p(x PROPN cana-844 202 22 ) ) PUNCT cana-844 202 23 indicates indicate VERB cana-844 202 24 the the DET cana-844 202 25 class class NOUN cana-844 202 26 's 's PART cana-844 202 27 prior prior ADJ cana-844 202 28 probability probability NOUN cana-844 202 29 . . PUNCT cana-844 203 1 p(y p(y PROPN cana-844 203 2 / / SYM cana-844 203 3 x x NOUN cana-844 203 4 ) ) PUNCT cana-844 203 5 shows show VERB cana-844 203 6 the the DET cana-844 203 7 likelihood likelihood NOUN cana-844 203 8 , , PUNCT cana-844 203 9 which which PRON cana-844 203 10 is be AUX cana-844 203 11 the the DET cana-844 203 12 probability probability NOUN cana-844 203 13 of of ADP cana-844 203 14 a a DET cana-844 203 15 predictor predictor NOUN cana-844 203 16 given give VERB cana-844 203 17 a a DET cana-844 203 18 class class NOUN cana-844 203 19 , , PUNCT cana-844 203 20 and and CCONJ cana-844 203 21 p(y p(y NOUN cana-844 203 22 ) ) PUNCT cana-844 203 23 represents represent VERB cana-844 203 24 the the DET cana-844 203 25 prior prior ADJ cana-844 203 26 probability probability NOUN cana-844 203 27 . . PUNCT cana-844 204 1 it it PRON cana-844 204 2 is be AUX cana-844 204 3 suitable suitable ADJ cana-844 204 4 for for ADP cana-844 204 5 both both CCONJ cana-844 204 6 binary binary NOUN cana-844 204 7 as as ADV cana-844 204 8 well well ADV cana-844 204 9 as as ADP cana-844 204 10 multi multi ADJ cana-844 204 11 - - ADJ cana-844 204 12 class class ADJ cana-844 204 13 classification classification NOUN cana-844 204 14 . . PUNCT cana-844 205 1 3.5.3 3.5.3 NUM cana-844 205 2 random random ADJ cana-844 205 3 forest forest NOUN cana-844 205 4 random random ADJ cana-844 205 5 forest forest NOUN cana-844 205 6 ( ( PUNCT cana-844 205 7 rf rf NOUN cana-844 205 8 ) ) PUNCT cana-844 205 9 is be AUX cana-844 205 10 a a DET cana-844 205 11 machine machine NOUN cana-844 205 12 - - PUNCT cana-844 205 13 learning learning NOUN cana-844 205 14 technique technique NOUN cana-844 205 15 that that PRON cana-844 205 16 constructs construct VERB cana-844 205 17 multiple multiple ADJ cana-844 205 18 decision decision NOUN cana-844 205 19 trees tree NOUN cana-844 205 20 using use VERB cana-844 205 21 training training NOUN cana-844 205 22 data datum NOUN cana-844 205 23 sets set NOUN cana-844 205 24 to to PART cana-844 205 25 create create VERB cana-844 205 26 a a DET cana-844 205 27 classification classification NOUN cana-844 205 28 model model NOUN cana-844 205 29 . . PUNCT cana-844 206 1 this this DET cana-844 206 2 method method NOUN cana-844 206 3 selects select VERB cana-844 206 4 trees tree NOUN cana-844 206 5 based base VERB cana-844 206 6 on on ADP cana-844 206 7 popular popular ADJ cana-844 206 8 choices choice NOUN cana-844 206 9 , , PUNCT cana-844 206 10 resulting result VERB cana-844 206 11 in in ADP cana-844 206 12 high high ADJ cana-844 206 13 accuracy accuracy NOUN cana-844 206 14 when when SCONJ cana-844 206 15 handling handle VERB cana-844 206 16 large large ADJ cana-844 206 17 data datum NOUN cana-844 206 18 sets set NOUN cana-844 206 19 [ [ X cana-844 206 20 25 25 NUM cana-844 206 21 ] ] PUNCT cana-844 206 22 . . PUNCT cana-844 207 1 the the DET cana-844 207 2 random random ADJ cana-844 207 3 forest forest NOUN cana-844 207 4 ( ( PUNCT cana-844 207 5 rf rf NOUN cana-844 207 6 ) ) PUNCT cana-844 207 7 is be AUX cana-844 207 8 a a DET cana-844 207 9 collection collection NOUN cana-844 207 10 of of ADP cana-844 207 11 tree tree NOUN cana-844 207 12 - - PUNCT cana-844 207 13 based base VERB cana-844 207 14 classifiers classifier NOUN cana-844 207 15 arranged arrange VERB cana-844 207 16 hierarchically hierarchically ADV cana-844 207 17 . . PUNCT cana-844 208 1 text text NOUN cana-844 208 2 data datum NOUN cana-844 208 3 often often ADV cana-844 208 4 have have VERB cana-844 208 5 numerous numerous ADJ cana-844 208 6 dimensions dimension NOUN cana-844 208 7 , , PUNCT cana-844 208 8 with with ADP cana-844 208 9 many many ADJ cana-844 208 10 irrelevant irrelevant ADJ cana-844 208 11 attributes attribute NOUN cana-844 208 12 in in ADP cana-844 208 13 the the DET cana-844 208 14 dataset dataset NOUN cana-844 208 15 . . PUNCT cana-844 209 1 only only ADV cana-844 209 2 a a DET cana-844 209 3 few few ADJ cana-844 209 4 important important ADJ cana-844 209 5 attributes attribute NOUN cana-844 209 6 provide provide VERB cana-844 209 7 information information NOUN cana-844 209 8 for for ADP cana-844 209 9 the the DET cana-844 209 10 classifier classifier PROPN cana-844 209 11 model model NOUN cana-844 209 12 . . PUNCT cana-844 210 1 the the DET cana-844 210 2 rf rf ADJ cana-844 210 3 algorithm algorithm NOUN cana-844 210 4 utilizes utilize VERB cana-844 210 5 a a DET cana-844 210 6 predetermined predetermined ADJ cana-844 210 7 probability probability NOUN cana-844 210 8 to to PART cana-844 210 9 select select VERB cana-844 210 10 the the DET cana-844 210 11 most most ADV cana-844 210 12 important important ADJ cana-844 210 13 relevant relevant ADJ cana-844 210 14 attribute attribute NOUN cana-844 210 15 . . PUNCT cana-844 211 1 breiman breiman PROPN cana-844 211 2 developed develop VERB cana-844 211 3 the the DET cana-844 211 4 rf rf ADJ cana-844 211 5 algorithm algorithm NOUN cana-844 211 6 by by ADP cana-844 211 7 using use VERB cana-844 211 8 sample sample NOUN cana-844 211 9 data datum NOUN cana-844 211 10 subsets subset NOUN cana-844 211 11 to to PART cana-844 211 12 create create VERB cana-844 211 13 multiple multiple ADJ cana-844 211 14 decision decision NOUN cana-844 211 15 trees tree NOUN cana-844 211 16 through through ADP cana-844 211 17 random random ADJ cana-844 211 18 feature feature NOUN cana-844 211 19 subspace subspace NOUN cana-844 211 20 sampling sampling NOUN cana-844 211 21 . . PUNCT cana-844 212 1 the the DET cana-844 212 2 rf rf ADJ cana-844 212 3 algorithm algorithm NOUN cana-844 212 4 , , PUNCT cana-844 212 5 linked link VERB cana-844 212 6 to to ADP cana-844 212 7 a a DET cana-844 212 8 set set NOUN cana-844 212 9 of of ADP cana-844 212 10 training training NOUN cana-844 212 11 documents document NOUN cana-844 212 12 d d NOUN cana-844 212 13 and and CCONJ cana-844 212 14 n n PROPN cana-844 212 15 features feature NOUN cana-844 212 16 , , PUNCT cana-844 212 17 can can AUX cana-844 212 18 be be AUX cana-844 212 19 outlined outline VERB cana-844 212 20 as as SCONJ cana-844 212 21 follows follow VERB cana-844 212 22 : : PUNCT cana-844 212 23 ( ( PUNCT cana-844 212 24 1)initialization 1)initialization NOUN cana-844 212 25 . . PUNCT cana-844 213 1 ( ( PUNCT cana-844 213 2 2 2 X cana-844 213 3 ) ) PUNCT cana-844 213 4 a a DET cana-844 213 5 decision decision NOUN cana-844 213 6 tree tree NOUN cana-844 213 7 model model NOUN cana-844 213 8 is be AUX cana-844 213 9 built build VERB cana-844 213 10 for for ADP cana-844 213 11 every every DET cana-844 213 12 document document NOUN cana-844 213 13 dk dk PROPN cana-844 213 14 . . PUNCT cana-844 213 15 training training NOUN cana-844 213 16 documents document NOUN cana-844 213 17 are be AUX cana-844 213 18 chosen choose VERB cana-844 213 19 at at ADP cana-844 213 20 random random ADJ cana-844 213 21 from from ADP cana-844 213 22 the the DET cana-844 213 23 available available ADJ cana-844 213 24 features feature NOUN cana-844 213 25 using use VERB cana-844 213 26 a a DET cana-844 213 27 subspace subspace NOUN cana-844 213 28 of of ADP cana-844 213 29 m m NOUN cana-844 213 30 - - PUNCT cana-844 213 31 try try VERB cana-844 213 32 dimension dimension NOUN cana-844 213 33 . . PUNCT cana-844 214 1 probabilities probability NOUN cana-844 214 2 are be AUX cana-844 214 3 calculated calculate VERB cana-844 214 4 based base VERB cana-844 214 5 on on ADP cana-844 214 6 all all DET cana-844 214 7 m m NOUN cana-844 214 8 - - PUNCT cana-844 214 9 try try VERB cana-844 214 10 features feature NOUN cana-844 214 11 . . PUNCT cana-844 215 1 the the DET cana-844 215 2 best good ADJ cana-844 215 3 data datum NOUN cana-844 215 4 split split NOUN cana-844 215 5 is be AUX cana-844 215 6 determined determine VERB cana-844 215 7 by by ADP cana-844 215 8 the the DET cana-844 215 9 leaf leaf NOUN cana-844 215 10 node node NOUN cana-844 215 11 . . PUNCT cana-844 216 1 this this DET cana-844 216 2 process process NOUN cana-844 216 3 is be AUX cana-844 216 4 repeated repeat VERB cana-844 216 5 until until SCONJ cana-844 216 6 the the DET cana-844 216 7 saturation saturation NOUN cana-844 216 8 criterion criterion NOUN cana-844 216 9 is be AUX cana-844 216 10 met meet VERB cana-844 216 11 . . PUNCT cana-844 217 1 ( ( PUNCT cana-844 217 2 3 3 X cana-844 217 3 ) ) PUNCT cana-844 217 4 merge merge VERB cana-844 217 5 the the DET cana-844 217 6 k k PROPN cana-844 217 7 unpruned unpruned PROPN cana-844 217 8 trees tree NOUN cana-844 217 9 h1(x1 h1(x1 NOUN cana-844 217 10 ) ) PUNCT cana-844 217 11 , , PUNCT cana-844 217 12 h2(x2), h2(x2), X cana-844 217 13 ...... ...... PUNCT cana-844 217 14 into into ADP cana-844 217 15 a a DET cana-844 217 16 random random ADJ cana-844 217 17 forest forest NOUN cana-844 217 18 group group NOUN cana-844 217 19 and and CCONJ cana-844 217 20 utilize utilize VERB cana-844 217 21 the the DET cana-844 217 22 highest high ADJ cana-844 217 23 probability probability NOUN cana-844 217 24 value value NOUN cana-844 217 25 for for ADP cana-844 217 26 making make VERB cana-844 217 27 classification classification NOUN cana-844 217 28 decisions decision NOUN cana-844 217 29 . . PUNCT cana-844 218 1 by by ADP cana-844 218 2 combining combine VERB cana-844 218 3 bagging bagging NOUN cana-844 218 4 and and CCONJ cana-844 218 5 random random ADJ cana-844 218 6 selection selection NOUN cana-844 218 7 , , PUNCT cana-844 218 8 rf rf NOUN cana-844 218 9 utilizes utilize VERB cana-844 218 10 two two NUM cana-844 218 11 feature feature NOUN cana-844 218 12 selection selection NOUN cana-844 218 13 methods method NOUN cana-844 218 14 to to PART cana-844 218 15 generate generate VERB cana-844 218 16 a a DET cana-844 218 17 more more ADV cana-844 218 18 efficient efficient ADJ cana-844 218 19 ensemble ensemble ADJ cana-844 218 20 model model NOUN cana-844 218 21 . . PUNCT cana-844 219 1 employing employ VERB cana-844 219 2 numerous numerous ADJ cana-844 219 3 trees tree NOUN cana-844 219 4 within within ADP cana-844 219 5 the the DET cana-844 219 6 rf rf NOUN cana-844 219 7 approach approach NOUN cana-844 219 8 reduces reduce VERB cana-844 219 9 the the DET cana-844 219 10 risk risk NOUN cana-844 219 11 of of ADP cana-844 219 12 overfitting overfitte VERB cana-844 219 13 and and CCONJ cana-844 219 14 decreases decrease VERB cana-844 219 15 training training NOUN cana-844 219 16 time time NOUN cana-844 219 17 . . PUNCT cana-844 220 1 additionally additionally ADV cana-844 220 2 , , PUNCT cana-844 220 3 rf rf PRON cana-844 220 4 provides provide VERB cana-844 220 5 estimates estimate NOUN cana-844 220 6 for for ADP cana-844 220 7 crucial crucial ADJ cana-844 220 8 classification classification NOUN cana-844 220 9 variables variable NOUN cana-844 220 10 and and CCONJ cana-844 220 11 missing miss VERB cana-844 220 12 data datum NOUN cana-844 220 13 , , PUNCT cana-844 220 14 ultimately ultimately ADV cana-844 220 15 enhancing enhance VERB cana-844 220 16 accuracy accuracy NOUN cana-844 220 17 . . PUNCT cana-844 221 1 3.5.4 3.5.4 NUM cana-844 221 2 logistic logistic ADJ cana-844 221 3 regression regression NOUN cana-844 221 4 logistic logistic ADJ cana-844 221 5 regression regression NOUN cana-844 221 6 is be AUX cana-844 221 7 employed employ VERB cana-844 221 8 to to PART cana-844 221 9 determine determine VERB cana-844 221 10 the the DET cana-844 221 11 connection connection NOUN cana-844 221 12 between between ADP cana-844 221 13 one one NUM cana-844 221 14 or or CCONJ cana-844 221 15 more more ADJ cana-844 221 16 predictor predictor NOUN cana-844 221 17 variables variable NOUN cana-844 221 18 and and CCONJ cana-844 221 19 a a DET cana-844 221 20 binary binary ADJ cana-844 221 21 outcome outcome NOUN cana-844 221 22 variable variable NOUN cana-844 221 23 . . PUNCT cana-844 222 1 a a DET cana-844 222 2 binary binary ADJ cana-844 222 3 variable variable NOUN cana-844 222 4 is be AUX cana-844 222 5 a a DET cana-844 222 6 type type NOUN cana-844 222 7 of of ADP cana-844 222 8 categorical categorical ADJ cana-844 222 9 variable variable NOUN cana-844 222 10 that that PRON cana-844 222 11 has have VERB cana-844 222 12 only only ADV cana-844 222 13 two two NUM cana-844 222 14 possible possible ADJ cana-844 222 15 values value NOUN cana-844 222 16 , , PUNCT cana-844 222 17 such such ADJ cana-844 222 18 as as ADP cana-844 222 19 0 0 NUM cana-844 222 20 or or CCONJ cana-844 222 21 1 1 NUM cana-844 222 22 . . PUNCT cana-844 223 1 logistic logistic ADJ cana-844 223 2 regression regression NOUN cana-844 223 3 extends extend VERB cana-844 223 4 linear linear PROPN cana-844 223 5 regression regression NOUN cana-844 223 6 by by ADP cana-844 223 7 assuming assume VERB cana-844 223 8 a a DET cana-844 223 9 linear linear ADJ cana-844 223 10 relationship relationship NOUN cana-844 223 11 between between ADP cana-844 223 12 the the DET cana-844 223 13 probability probability NOUN cana-844 223 14 of of ADP cana-844 223 15 the the DET cana-844 223 16 outcome outcome NOUN cana-844 223 17 and and CCONJ cana-844 223 18 the the DET cana-844 223 19 independent independent ADJ cana-844 223 20 variable variable NOUN cana-844 223 21 ( ( PUNCT cana-844 223 22 x x NOUN cana-844 223 23 ) ) PUNCT cana-844 223 24 , , PUNCT cana-844 223 25 avoiding avoid VERB cana-844 223 26 communications communication NOUN cana-844 223 27 on on ADP cana-844 223 28 applied apply VERB cana-844 223 29 nonlinear nonlinear ADJ cana-844 223 30 analysis analysis NOUN cana-844 223 31 issn issn NOUN cana-844 223 32 : : PUNCT cana-844 223 33 1074 1074 NUM cana-844 223 34 - - PUNCT cana-844 223 35 133x 133x NUM cana-844 223 36 vol vol NOUN cana-844 223 37 31 31 NUM cana-844 223 38 no no NOUN cana-844 223 39 . . PUNCT cana-844 224 1 4s 4s NUM cana-844 224 2 ( ( PUNCT cana-844 224 3 2024 2024 NUM cana-844 224 4 ) ) PUNCT cana-844 224 5 241 241 NUM cana-844 224 6 https://internationalpubls.com https://internationalpubls.com X cana-844 224 7 predicted predict VERB cana-844 224 8 probabilities probability NOUN cana-844 224 9 beyond beyond ADP cana-844 224 10 0 0 NUM cana-844 224 11 - - SYM cana-844 224 12 1 1 NUM cana-844 224 13 range range NOUN cana-844 224 14 . . PUNCT cana-844 225 1 the the DET cana-844 225 2 intercept intercept NOUN cana-844 225 3 ( ( PUNCT cana-844 225 4 b0 b0 NOUN cana-844 225 5 ) ) PUNCT cana-844 225 6 and and CCONJ cana-844 225 7 slope slope NOUN cana-844 225 8 ( ( PUNCT cana-844 225 9 b1 b1 NOUN cana-844 225 10 ) ) PUNCT cana-844 225 11 of of ADP cana-844 225 12 this this DET cana-844 225 13 line line NOUN cana-844 225 14 are be AUX cana-844 225 15 represented represent VERB cana-844 225 16 by by ADP cana-844 225 17 the the DET cana-844 225 18 regression regression NOUN cana-844 225 19 coefficient coefficient NOUN cana-844 225 20 which which PRON cana-844 225 21 is be AUX cana-844 225 22 shown show VERB cana-844 225 23 in in ADP cana-844 225 24 equation equation NOUN cana-844 225 25 4 4 NUM cana-844 225 26 . . PUNCT cana-844 225 27 ln ln ADJ cana-844 225 28 ( ( PUNCT cana-844 225 29 p/(1 p/(1 NUM cana-844 225 30 - - PUNCT cana-844 225 31 p))= p))= PROPN cana-844 225 32 b0 b0 NOUN cana-844 225 33 + + CCONJ cana-844 225 34 b1x b1x PROPN cana-844 225 35 ( ( PUNCT cana-844 225 36 4 4 X cana-844 225 37 ) ) PUNCT cana-844 225 38 solving solve VERB cana-844 225 39 for for ADP cana-844 225 40 the the DET cana-844 225 41 probability probability NOUN cana-844 225 42 in in ADP cana-844 225 43 this this DET cana-844 225 44 equation equation NOUN cana-844 225 45 reveals reveal VERB cana-844 225 46 a a DET cana-844 225 47 sigmoidal sigmoidal NOUN cana-844 225 48 relationship relationship NOUN cana-844 225 49 with with ADP cana-844 225 50 the the DET cana-844 225 51 independent independent ADJ cana-844 225 52 variable variable NOUN cana-844 225 53 , , PUNCT cana-844 225 54 restricting restrict VERB cana-844 225 55 the the DET cana-844 225 56 estimated estimate VERB cana-844 225 57 probabilities probability NOUN cana-844 225 58 to to ADP cana-844 225 59 a a DET cana-844 225 60 range range NOUN cana-844 225 61 of of ADP cana-844 225 62 0 0 NUM cana-844 225 63 to to PART cana-844 225 64 1 1 NUM cana-844 226 1 [ [ X cana-844 226 2 26 26 NUM cana-844 226 3 ] ] PUNCT cana-844 226 4 . . PUNCT cana-844 227 1 logistic logistic ADJ cana-844 227 2 regression regression NOUN cana-844 227 3 is be AUX cana-844 227 4 effective effective ADJ cana-844 227 5 even even ADV cana-844 227 6 with with ADP cana-844 227 7 small small ADJ cana-844 227 8 datasets dataset NOUN cana-844 227 9 , , PUNCT cana-844 227 10 making make VERB cana-844 227 11 it it PRON cana-844 227 12 ideal ideal ADJ cana-844 227 13 for for ADP cana-844 227 14 situations situation NOUN cana-844 227 15 with with ADP cana-844 227 16 limited limited ADJ cana-844 227 17 or or CCONJ cana-844 227 18 costly costly ADJ cana-844 227 19 data datum NOUN cana-844 227 20 collection collection NOUN cana-844 227 21 . . PUNCT cana-844 228 1 it it PRON cana-844 228 2 supports support VERB cana-844 228 3 regularization regularization NOUN cana-844 228 4 methods method NOUN cana-844 228 5 that that PRON cana-844 228 6 prevent prevent VERB cana-844 228 7 overfitting overfitting NOUN cana-844 228 8 and and CCONJ cana-844 228 9 enhance enhance VERB cana-844 228 10 generalization generalization NOUN cana-844 228 11 by by ADP cana-844 228 12 penalizing penalize VERB cana-844 228 13 large large ADJ cana-844 228 14 coefficient coefficient NOUN cana-844 228 15 values value NOUN cana-844 228 16 . . PUNCT cana-844 229 1 logistic logistic ADJ cana-844 229 2 regression regression NOUN cana-844 229 3 is be AUX cana-844 229 4 capable capable ADJ cana-844 229 5 of of ADP cana-844 229 6 managing manage VERB cana-844 229 7 datasets dataset NOUN cana-844 229 8 with with ADP cana-844 229 9 numerous numerous ADJ cana-844 229 10 irrelevant irrelevant ADJ cana-844 229 11 or or CCONJ cana-844 229 12 weakly weakly ADJ cana-844 229 13 correlated correlate VERB cana-844 229 14 features feature NOUN cana-844 229 15 . . PUNCT cana-844 230 1 3.5.5 3.5.5 NUM cana-844 230 2 sequential sequential ADJ cana-844 230 3 fcnet fcnet ADJ cana-844 230 4 artificial artificial ADJ cana-844 230 5 neural neural ADJ cana-844 230 6 network network NOUN cana-844 230 7 artificial artificial ADJ cana-844 230 8 neural neural ADJ cana-844 230 9 networks network NOUN cana-844 230 10 , , PUNCT cana-844 230 11 often often ADV cana-844 230 12 referred refer VERB cana-844 230 13 to to ADP cana-844 230 14 as as ADP cana-844 230 15 neural neural ADJ cana-844 230 16 networks network NOUN cana-844 230 17 , , PUNCT cana-844 230 18 are be AUX cana-844 230 19 mathematical mathematical ADJ cana-844 230 20 or or CCONJ cana-844 230 21 computational computational ADJ cana-844 230 22 models model NOUN cana-844 230 23 inspired inspire VERB cana-844 230 24 by by ADP cana-844 230 25 the the DET cana-844 230 26 structure structure NOUN cana-844 230 27 and and CCONJ cana-844 230 28 function function NOUN cana-844 230 29 of of ADP cana-844 230 30 biological biological ADJ cana-844 230 31 neural neural ADJ cana-844 230 32 networks network NOUN cana-844 230 33 . . PUNCT cana-844 231 1 a a DET cana-844 231 2 neural neural ADJ cana-844 231 3 network network NOUN cana-844 231 4 consists consist VERB cana-844 231 5 of of ADP cana-844 231 6 a a DET cana-844 231 7 connected connected ADJ cana-844 231 8 group group NOUN cana-844 231 9 of of ADP cana-844 231 10 artificial artificial ADJ cana-844 231 11 neurons neuron NOUN cana-844 231 12 , , PUNCT cana-844 231 13 which which PRON cana-844 231 14 work work VERB cana-844 231 15 together together ADV cana-844 231 16 to to PART cana-844 231 17 solve solve VERB cana-844 231 18 particular particular ADJ cana-844 231 19 problems problem NOUN cana-844 231 20 [ [ X cana-844 231 21 27 27 NUM cana-844 231 22 ] ] PUNCT cana-844 231 23 . . PUNCT cana-844 232 1 the the DET cana-844 232 2 neuron neuron NOUN cana-844 232 3 operates operate VERB cana-844 232 4 in in ADP cana-844 232 5 two two NUM cana-844 232 6 modes mode NOUN cana-844 232 7 : : PUNCT cana-844 232 8 the the DET cana-844 232 9 training training NOUN cana-844 232 10 / / SYM cana-844 232 11 learning learn VERB cana-844 232 12 mode mode NOUN cana-844 232 13 and and CCONJ cana-844 232 14 the the DET cana-844 232 15 using use VERB cana-844 232 16 / / SYM cana-844 232 17 testing testing NOUN cana-844 232 18 mode mode NOUN cana-844 232 19 . . PUNCT cana-844 233 1 in in ADP cana-844 233 2 most most ADJ cana-844 233 3 cases case NOUN cana-844 233 4 , , PUNCT cana-844 233 5 an an DET cana-844 233 6 ann ann PROPN cana-844 233 7 is be AUX cana-844 233 8 an an DET cana-844 233 9 adaptive adaptive ADJ cana-844 233 10 system system NOUN cana-844 233 11 that that PRON cana-844 233 12 adjusts adjust VERB cana-844 233 13 its its PRON cana-844 233 14 structure structure NOUN cana-844 233 15 based base VERB cana-844 233 16 on on ADP cana-844 233 17 information information NOUN cana-844 233 18 from from ADP cana-844 233 19 the the DET cana-844 233 20 network network NOUN cana-844 233 21 during during ADP cana-844 233 22 the the DET cana-844 233 23 learning learning NOUN cana-844 233 24 phase phase NOUN cana-844 233 25 . . PUNCT cana-844 234 1 modern modern ADJ cana-844 234 2 neural neural ADJ cana-844 234 3 networks network NOUN cana-844 234 4 are be AUX cana-844 234 5 tools tool NOUN cana-844 234 6 for for ADP cana-844 234 7 modelling model VERB cana-844 234 8 non non ADJ cana-844 234 9 - - ADJ cana-844 234 10 linear linear ADJ cana-844 234 11 statistical statistical ADJ cana-844 234 12 data datum NOUN cana-844 234 13 , , PUNCT cana-844 234 14 commonly commonly ADV cana-844 234 15 used use VERB cana-844 234 16 to to PART cana-844 234 17 represent represent VERB cana-844 234 18 intricate intricate ADJ cana-844 234 19 relationships relationship NOUN cana-844 234 20 between between ADP cana-844 234 21 inputs input NOUN cana-844 234 22 and and CCONJ cana-844 234 23 outputs output NOUN cana-844 234 24 or or CCONJ cana-844 234 25 to to PART cana-844 234 26 identify identify VERB cana-844 234 27 patterns pattern NOUN cana-844 234 28 in in ADP cana-844 234 29 data datum NOUN cana-844 234 30 . . PUNCT cana-844 235 1 the the DET cana-844 235 2 structure structure NOUN cana-844 235 3 of of ADP cana-844 235 4 feedforward feedforward ADJ cana-844 235 5 neural neural ADJ cana-844 235 6 network network NOUN cana-844 235 7 is be AUX cana-844 235 8 shown show VERB cana-844 235 9 in in ADP cana-844 235 10 fig fig NOUN cana-844 235 11 5 5 NUM cana-844 235 12 . . PUNCT cana-844 235 13 fig fig NOUN cana-844 235 14 5 5 NUM cana-844 235 15 : : PUNCT cana-844 235 16 structure structure NOUN cana-844 235 17 of of ADP cana-844 235 18 feedforward feedforward ADJ cana-844 235 19 neural neural ADJ cana-844 235 20 network network NOUN cana-844 235 21 the the DET cana-844 235 22 back back ADJ cana-844 235 23 propagation propagation NOUN cana-844 235 24 learning learn VERB cana-844 235 25 algorithm algorithm NOUN cana-844 235 26 is be AUX cana-844 235 27 a a DET cana-844 235 28 key key ADJ cana-844 235 29 advancement advancement NOUN cana-844 235 30 in in ADP cana-844 235 31 neural neural ADJ cana-844 235 32 networks network NOUN cana-844 235 33 . . PUNCT cana-844 236 1 it it PRON cana-844 236 2 is be AUX cana-844 236 3 a a DET cana-844 236 4 supervised supervised ADJ cana-844 236 5 learning learning NOUN cana-844 236 6 method method NOUN cana-844 236 7 commonly commonly ADV cana-844 236 8 used use VERB cana-844 236 9 in in ADP cana-844 236 10 multilayer multilayer ADJ cana-844 236 11 feed feed NOUN cana-844 236 12 - - PUNCT cana-844 236 13 forward forward NOUN cana-844 236 14 networks network NOUN cana-844 236 15 with with ADP cana-844 236 16 continuous continuous ADJ cana-844 236 17 differentiable differentiable ADJ cana-844 236 18 activation activation NOUN cana-844 236 19 functions function NOUN cana-844 236 20 such such ADJ cana-844 236 21 as as ADP cana-844 236 22 tan tan NOUN cana-844 236 23 - - PUNCT cana-844 236 24 sigmoid sigmoid NOUN cana-844 236 25 and and CCONJ cana-844 236 26 log log NOUN cana-844 236 27 - - PUNCT cana-844 236 28 sigmoid sigmoid NOUN cana-844 236 29 . . PUNCT cana-844 237 1 these these DET cana-844 237 2 networks network NOUN cana-844 237 3 , , PUNCT cana-844 237 4 known know VERB cana-844 237 5 as as ADP cana-844 237 6 backpropagation backpropagation NOUN cana-844 237 7 learning learning NOUN cana-844 237 8 networks network NOUN cana-844 237 9 ( ( PUNCT cana-844 237 10 bpns bpns NOUN cana-844 237 11 ) ) PUNCT cana-844 237 12 , , PUNCT cana-844 237 13 adjust adjust VERB cana-844 237 14 weights weight NOUN cana-844 237 15 to to PART cana-844 237 16 categorize categorize VERB cana-844 237 17 inputs input NOUN cana-844 237 18 correctly correctly ADV cana-844 237 19 based base VERB cana-844 237 20 on on ADP cana-844 237 21 a a DET cana-844 237 22 provided provide VERB cana-844 237 23 set set NOUN cana-844 237 24 of of ADP cana-844 237 25 training training NOUN cana-844 237 26 input input NOUN cana-844 237 27 - - PUNCT cana-844 237 28 output output NOUN cana-844 237 29 pairs pair NOUN cana-844 237 30 . . PUNCT cana-844 238 1 this this DET cana-844 238 2 process process NOUN cana-844 238 3 involves involve VERB cana-844 238 4 a a DET cana-844 238 5 gradient gradient ADJ cana-844 238 6 - - PUNCT cana-844 238 7 descent descent NOUN cana-844 238 8 method method NOUN cana-844 238 9 similar similar ADJ cana-844 238 10 to to ADP cana-844 238 11 simple simple ADJ cana-844 238 12 perceptron perceptron PROPN cana-844 238 13 networks network NOUN cana-844 238 14 . . PUNCT cana-844 239 1 by by ADP cana-844 239 2 sending send VERB cana-844 239 3 errors error NOUN cana-844 239 4 back back ADV cana-844 239 5 to to ADP cana-844 239 6 hidden hidden ADJ cana-844 239 7 units unit NOUN cana-844 239 8 , , PUNCT cana-844 239 9 the the DET cana-844 239 10 algorithm algorithm NOUN cana-844 239 11 aims aim VERB cana-844 239 12 to to PART cana-844 239 13 find find VERB cana-844 239 14 a a DET cana-844 239 15 balance balance NOUN cana-844 239 16 between between ADP cana-844 239 17 memorization memorization NOUN cana-844 239 18 and and CCONJ cana-844 239 19 generalization generalization NOUN cana-844 239 20 . . PUNCT cana-844 240 1 this this DET cana-844 240 2 balance balance NOUN cana-844 240 3 enables enable VERB cana-844 240 4 the the DET cana-844 240 5 network network NOUN cana-844 240 6 to to PART cana-844 240 7 respond respond VERB cana-844 240 8 accurately accurately ADV cana-844 240 9 to to ADP cana-844 240 10 both both CCONJ cana-844 240 11 familiar familiar ADJ cana-844 240 12 inputs input NOUN cana-844 240 13 and and CCONJ cana-844 240 14 those those PRON cana-844 240 15 that that PRON cana-844 240 16 are be AUX cana-844 240 17 similar similar ADJ cana-844 240 18 yet yet CCONJ cana-844 240 19 distinct distinct ADJ cana-844 240 20 . . PUNCT cana-844 241 1 4 4 X cana-844 241 2 . . X cana-844 241 3 performance performance NOUN cana-844 241 4 evaluation evaluation NOUN cana-844 241 5 metrics metric NOUN cana-844 241 6 when when SCONJ cana-844 241 7 doing do VERB cana-844 241 8 binary binary ADJ cana-844 241 9 classification classification NOUN cana-844 241 10 , , PUNCT cana-844 241 11 data datum NOUN cana-844 241 12 instances instance NOUN cana-844 241 13 are be AUX cana-844 241 14 usually usually ADV cana-844 241 15 predicted predict VERB cana-844 241 16 as as ADP cana-844 241 17 either either CCONJ cana-844 241 18 positive positive ADJ cana-844 241 19 or or CCONJ cana-844 241 20 negative negative ADJ cana-844 241 21 . . PUNCT cana-844 242 1 a a DET cana-844 242 2 positive positive ADJ cana-844 242 3 label label NOUN cana-844 242 4 indicates indicate VERB cana-844 242 5 the the DET cana-844 242 6 presence presence NOUN cana-844 242 7 of of ADP cana-844 242 8 illness illness NOUN cana-844 242 9 , , PUNCT cana-844 242 10 abnormality abnormality NOUN cana-844 242 11 , , PUNCT cana-844 242 12 or or CCONJ cana-844 242 13 deviation deviation NOUN cana-844 242 14 , , PUNCT cana-844 242 15 while while SCONJ cana-844 242 16 a a DET cana-844 242 17 negative negative ADJ cana-844 242 18 label label NOUN cana-844 242 19 means mean VERB cana-844 242 20 communications communication NOUN cana-844 242 21 on on ADP cana-844 242 22 applied apply VERB cana-844 242 23 nonlinear nonlinear ADJ cana-844 242 24 analysis analysis NOUN cana-844 242 25 issn issn NOUN cana-844 242 26 : : PUNCT cana-844 242 27 1074 1074 NUM cana-844 242 28 - - PUNCT cana-844 242 29 133x 133x NUM cana-844 242 30 vol vol NOUN cana-844 242 31 31 31 NUM cana-844 242 32 no no NOUN cana-844 242 33 . . PUNCT cana-844 243 1 4s 4s NUM cana-844 243 2 ( ( PUNCT cana-844 243 3 2024 2024 NUM cana-844 243 4 ) ) PUNCT cana-844 243 5 242 242 NUM cana-844 243 6 https://internationalpubls.com https://internationalpubls.com X cana-844 243 7 there there PRON cana-844 243 8 is be VERB cana-844 243 9 no no DET cana-844 243 10 difference difference NOUN cana-844 243 11 from from ADP cana-844 243 12 the the DET cana-844 243 13 baseline baseline NOUN cana-844 243 14 . . PUNCT cana-844 244 1 as as ADP cana-844 244 2 a a DET cana-844 244 3 result result NOUN cana-844 244 4 , , PUNCT cana-844 244 5 each each DET cana-844 244 6 binary binary ADJ cana-844 244 7 label label NOUN cana-844 244 8 prediction prediction NOUN cana-844 244 9 can can AUX cana-844 244 10 have have VERB cana-844 244 11 four four NUM cana-844 244 12 potential potential ADJ cana-844 244 13 outcomesa outcomesa NOUN cana-844 244 14 true true ADJ cana-844 244 15 positive positive ADJ cana-844 244 16 ( ( PUNCT cana-844 244 17 tp tp NOUN cana-844 244 18 ) ) PUNCT cana-844 244 19 occurs occur VERB cana-844 244 20 when when SCONJ cana-844 244 21 a a DET cana-844 244 22 positive positive ADJ cana-844 244 23 outcome outcome NOUN cana-844 244 24 is be AUX cana-844 244 25 predicted predict VERB cana-844 244 26 correctly correctly ADV cana-844 244 27 . . PUNCT cana-844 245 1 on on ADP cana-844 245 2 the the DET cana-844 245 3 other other ADJ cana-844 245 4 hand hand NOUN cana-844 245 5 , , PUNCT cana-844 245 6 a a DET cana-844 245 7 false false ADJ cana-844 245 8 positive positive ADJ cana-844 245 9 ( ( PUNCT cana-844 245 10 fp fp NOUN cana-844 245 11 ) ) PUNCT cana-844 245 12 happens happen VERB cana-844 245 13 when when SCONJ cana-844 245 14 a a DET cana-844 245 15 negative negative ADJ cana-844 245 16 instance instance NOUN cana-844 245 17 is be AUX cana-844 245 18 incorrectly incorrectly ADV cana-844 245 19 predicted predict VERB cana-844 245 20 as as ADP cana-844 245 21 positive positive ADJ cana-844 245 22 . . PUNCT cana-844 246 1 a a DET cana-844 246 2 true true ADJ cana-844 246 3 negative negative ADJ cana-844 246 4 ( ( PUNCT cana-844 246 5 tn tn NOUN cana-844 246 6 ) ) PUNCT cana-844 246 7 is be AUX cana-844 246 8 when when SCONJ cana-844 246 9 a a DET cana-844 246 10 negative negative ADJ cana-844 246 11 outcome outcome NOUN cana-844 246 12 is be AUX cana-844 246 13 predicted predict VERB cana-844 246 14 accurately accurately ADV cana-844 246 15 ; ; PUNCT cana-844 246 16 while while SCONJ cana-844 246 17 a a DET cana-844 246 18 false false ADJ cana-844 246 19 negative negative ADJ cana-844 246 20 ( ( PUNCT cana-844 246 21 fn fn NOUN cana-844 246 22 ) ) PUNCT cana-844 246 23 is be AUX cana-844 246 24 when when SCONJ cana-844 246 25 a a DET cana-844 246 26 positive positive ADJ cana-844 246 27 instance instance NOUN cana-844 246 28 is be AUX cana-844 246 29 wrongly wrongly ADV cana-844 246 30 predicted predict VERB cana-844 246 31 as as ADP cana-844 246 32 negative negative ADJ cana-844 246 33 . . PUNCT cana-844 247 1 the the DET cana-844 247 2 evaluation evaluation NOUN cana-844 247 3 metrics metric NOUN cana-844 247 4 most most ADV cana-844 247 5 frequently frequently ADV cana-844 247 6 used use VERB cana-844 247 7 for for ADP cana-844 247 8 binary binary ADJ cana-844 247 9 classification classification NOUN cana-844 247 10 are be AUX cana-844 247 11 sensitivity sensitivity NOUN cana-844 247 12 , , PUNCT cana-844 247 13 accuracy accuracy NOUN cana-844 247 14 , , PUNCT cana-844 247 15 precision precision NOUN cana-844 247 16 , , PUNCT cana-844 247 17 and and CCONJ cana-844 247 18 specificity specificity NOUN cana-844 247 19 . . PUNCT cana-844 248 1 these these DET cana-844 248 2 metrics metric NOUN cana-844 248 3 indicate indicate VERB cana-844 248 4 the the DET cana-844 248 5 percentage percentage NOUN cana-844 248 6 of of ADP cana-844 248 7 correctly correctly ADV cana-844 248 8 classified classified ADJ cana-844 248 9 instances instance NOUN cana-844 248 10 in in ADP cana-844 248 11 the the DET cana-844 248 12 total total ADJ cana-844 248 13 set set NOUN cana-844 248 14 of of ADP cana-844 248 15 instances instance NOUN cana-844 248 16 , , PUNCT cana-844 248 17 the the DET cana-844 248 18 actual actual ADJ cana-844 248 19 positive positive ADJ cana-844 248 20 instances instance NOUN cana-844 248 21 , , PUNCT cana-844 248 22 the the DET cana-844 248 23 actual actual ADJ cana-844 248 24 negative negative ADJ cana-844 248 25 instances instance NOUN cana-844 248 26 , , PUNCT cana-844 248 27 or or CCONJ cana-844 248 28 the the DET cana-844 248 29 instances instance NOUN cana-844 248 30 identified identify VERB cana-844 248 31 as as ADP cana-844 248 32 positive positive ADJ cana-844 248 33 , , PUNCT cana-844 248 34 respectively respectively ADV cana-844 248 35 [ [ X cana-844 248 36 28 28 NUM cana-844 248 37 ] ] PUNCT cana-844 248 38 . . PUNCT cana-844 249 1 their their PRON cana-844 249 2 formulas formula NOUN cana-844 249 3 are be AUX cana-844 249 4 mentioned mention VERB cana-844 249 5 in in ADP cana-844 249 6 equation equation NOUN cana-844 249 7 ( ( PUNCT cana-844 249 8 4 4 NUM cana-844 249 9 - - SYM cana-844 249 10 7 7 NUM cana-844 249 11 ) ) PUNCT cana-844 249 12 as as SCONJ cana-844 249 13 given give VERB cana-844 249 14 below below ADV cana-844 249 15 : : PUNCT cana-844 249 16 acc acc PROPN cana-844 249 17 = = NOUN cana-844 249 18 𝑇𝑃+𝑇𝑁 𝑇𝑃+𝑇𝑁 X cana-844 249 19 𝑇𝑃+𝑇𝑁+𝐹𝑃+𝐹𝑁 𝑇𝑃+𝑇𝑁+𝐹𝑃+𝐹𝑁 PUNCT cana-844 249 20 ( ( PUNCT cana-844 249 21 4 4 X cana-844 249 22 ) ) PUNCT cana-844 249 23 sen sen NOUN cana-844 249 24 = = PUNCT cana-844 249 25 𝑇𝑃 𝑇𝑃 PROPN cana-844 249 26 𝑇𝑃+𝐹𝑁 𝑇𝑃+𝐹𝑁 NOUN cana-844 249 27 ( ( PUNCT cana-844 249 28 5 5 NUM cana-844 249 29 ) ) PUNCT cana-844 249 30 spec spec NOUN cana-844 249 31 = = SYM cana-844 249 32 𝑇𝑁 𝑇𝑁 PROPN cana-844 249 33 𝑇𝑁+𝐹𝑃 𝑇𝑁+𝐹𝑃 NOUN cana-844 249 34 ( ( PUNCT cana-844 249 35 6 6 NUM cana-844 249 36 ) ) PUNCT cana-844 249 37 pre pre X cana-844 250 1 = = NOUN cana-844 250 2 ⁑ ⁑ NUM cana-844 250 3 𝑇𝑃 𝑇𝑃 PROPN cana-844 250 4 𝑇𝑃+𝐹𝑃 𝑇𝑃+𝐹𝑃 NUM cana-844 250 5 ( ( PUNCT cana-844 250 6 7 7 NUM cana-844 250 7 ) ) PUNCT cana-844 250 8 in in ADP cana-844 250 9 addition addition NOUN cana-844 250 10 to to ADP cana-844 250 11 accuracy accuracy NOUN cana-844 250 12 , , PUNCT cana-844 250 13 the the DET cana-844 250 14 mentioned mention VERB cana-844 250 15 metrics metric NOUN cana-844 250 16 are be AUX cana-844 250 17 commonly commonly ADV cana-844 250 18 paired pair VERB cana-844 250 19 together together ADV cana-844 250 20 , , PUNCT cana-844 250 21 like like ADP cana-844 250 22 precision precision NOUN cana-844 250 23 and and CCONJ cana-844 250 24 recall recall NOUN cana-844 250 25 or or CCONJ cana-844 250 26 sensitivity sensitivity NOUN cana-844 250 27 and and CCONJ cana-844 250 28 specificity specificity NOUN cana-844 250 29 . . PUNCT cana-844 251 1 sensitivity sensitivity NOUN cana-844 251 2 and and CCONJ cana-844 251 3 specificity specificity NOUN cana-844 251 4 can can AUX cana-844 251 5 provide provide VERB cana-844 251 6 more more ADJ cana-844 251 7 insights insight NOUN cana-844 251 8 into into ADP cana-844 251 9 the the DET cana-844 251 10 model model NOUN cana-844 251 11 compared compare VERB cana-844 251 12 to to ADP cana-844 251 13 accuracy accuracy NOUN cana-844 251 14 , , PUNCT cana-844 251 15 especially especially ADV cana-844 251 16 when when SCONJ cana-844 251 17 there there PRON cana-844 251 18 is be VERB cana-844 251 19 a a DET cana-844 251 20 significant significant ADJ cana-844 251 21 imbalance imbalance NOUN cana-844 251 22 in in ADP cana-844 251 23 the the DET cana-844 251 24 number number NOUN cana-844 251 25 of of ADP cana-844 251 26 true true ADJ cana-844 251 27 positive positive ADJ cana-844 251 28 and and CCONJ cana-844 251 29 negative negative ADJ cana-844 251 30 instances instance NOUN cana-844 251 31 . . PUNCT cana-844 252 1 additionally additionally ADV cana-844 252 2 , , PUNCT cana-844 252 3 there there PRON cana-844 252 4 are be VERB cana-844 252 5 various various ADJ cana-844 252 6 evaluation evaluation NOUN cana-844 252 7 metrics metric NOUN cana-844 252 8 , , PUNCT cana-844 252 9 such such ADJ cana-844 252 10 as as ADP cana-844 252 11 the the DET cana-844 252 12 f1 f1 NOUN cana-844 252 13 - - PUNCT cana-844 252 14 score score NOUN cana-844 252 15 , , PUNCT cana-844 252 16 that that PRON cana-844 252 17 rely rely VERB cana-844 252 18 on on ADP cana-844 252 19 the the DET cana-844 252 20 combined combine VERB cana-844 252 21 values value NOUN cana-844 252 22 of of ADP cana-844 252 23 precision precision NOUN cana-844 252 24 and and CCONJ cana-844 252 25 recall recall NOUN cana-844 252 26 . . PUNCT cana-844 253 1 the the DET cana-844 253 2 formula formula NOUN cana-844 253 3 for for ADP cana-844 253 4 f1 f1 NOUN cana-844 253 5 - - PUNCT cana-844 253 6 score score NOUN cana-844 253 7 is be AUX cana-844 253 8 mentioned mention VERB cana-844 253 9 in in ADP cana-844 253 10 equation equation NOUN cana-844 253 11 8 8 NUM cana-844 253 12 [ [ X cana-844 253 13 29 29 NUM cana-844 253 14 ] ] PUNCT cana-844 253 15 . . PUNCT cana-844 254 1 f1 f1 NOUN cana-844 254 2 - - PUNCT cana-844 254 3 score score NOUN cana-844 254 4 = = SYM cana-844 254 5 2βˆ—π‘ƒπ‘Ÿπ‘’βˆ—π‘†π‘’π‘› 2βˆ—π‘ƒπ‘Ÿπ‘’βˆ—π‘†π‘’π‘› NUM cana-844 254 6 π‘ƒπ‘Ÿπ‘’+𝑆𝑒𝑛 π‘ƒπ‘Ÿπ‘’+𝑆𝑒𝑛 X cana-844 254 7 ( ( PUNCT cana-844 254 8 8) 8) NUM cana-844 254 9 these these DET cana-844 254 10 measurements measurement NOUN cana-844 254 11 offer offer VERB cana-844 254 12 valuable valuable ADJ cana-844 254 13 information information NOUN cana-844 254 14 on on ADP cana-844 254 15 various various ADJ cana-844 254 16 aspects aspect NOUN cana-844 254 17 of of ADP cana-844 254 18 model model NOUN cana-844 254 19 performance performance NOUN cana-844 254 20 , , PUNCT cana-844 254 21 aiding aid VERB cana-844 254 22 in in ADP cana-844 254 23 informed informed ADJ cana-844 254 24 decision decision NOUN cana-844 254 25 - - PUNCT cana-844 254 26 making making NOUN cana-844 254 27 throughout throughout ADP cana-844 254 28 the the DET cana-844 254 29 model model NOUN cana-844 254 30 evaluation evaluation NOUN cana-844 254 31 process process NOUN cana-844 254 32 . . PUNCT cana-844 255 1 5 5 X cana-844 255 2 . . X cana-844 255 3 result result VERB cana-844 255 4 analysis analysis NOUN cana-844 255 5 the the DET cana-844 255 6 purpose purpose NOUN cana-844 255 7 of of ADP cana-844 255 8 this this DET cana-844 255 9 analysis analysis NOUN cana-844 255 10 is be AUX cana-844 255 11 to to PART cana-844 255 12 evaluate evaluate VERB cana-844 255 13 how how SCONJ cana-844 255 14 well well ADV cana-844 255 15 different different ADJ cana-844 255 16 predictive predictive ADJ cana-844 255 17 models model NOUN cana-844 255 18 perform perform VERB cana-844 255 19 by by ADP cana-844 255 20 using use VERB cana-844 255 21 various various ADJ cana-844 255 22 performance performance NOUN cana-844 255 23 evaluation evaluation NOUN cana-844 255 24 metrics metric NOUN cana-844 255 25 . . PUNCT cana-844 256 1 5.1 5.1 NUM cana-844 256 2 vgg19 vgg19 NOUN cana-844 256 3 image image NOUN cana-844 256 4 classification classification NOUN cana-844 256 5 with with ADP cana-844 256 6 various various ADJ cana-844 256 7 classifiers classifier NOUN cana-844 256 8 the the DET cana-844 256 9 analysis analysis NOUN cana-844 256 10 shows show VERB cana-844 256 11 how how SCONJ cana-844 256 12 different different ADJ cana-844 256 13 algorithms algorithm NOUN cana-844 256 14 perform perform VERB cana-844 256 15 when when SCONJ cana-844 256 16 using use VERB cana-844 256 17 vgg19 vgg19 NOUN cana-844 256 18 features feature NOUN cana-844 256 19 . . PUNCT cana-844 257 1 sequential sequential ADJ cana-844 257 2 ann ann PROPN cana-844 257 3 for for ADP cana-844 257 4 vgg19 vgg19 PROPN cana-844 257 5 achieved achieve VERB cana-844 257 6 the the DET cana-844 257 7 highest high ADJ cana-844 257 8 accuracy accuracy NOUN cana-844 257 9 at at ADP cana-844 257 10 96.30 96.30 NUM cana-844 257 11 % % NOUN cana-844 257 12 , , PUNCT cana-844 257 13 followed follow VERB cana-844 257 14 closely closely ADV cana-844 257 15 by by ADP cana-844 257 16 random random ADJ cana-844 257 17 forest forest NOUN cana-844 257 18 classifier classifier NOUN cana-844 257 19 at at ADP cana-844 257 20 95.58 95.58 NUM cana-844 257 21 % % NOUN cana-844 257 22 . . PUNCT cana-844 258 1 naΓ―ve naΓ―ve ADJ cana-844 258 2 bayes bayes PROPN cana-844 258 3 and and CCONJ cana-844 258 4 knn knn PROPN cana-844 258 5 algorithms algorithm NOUN cana-844 258 6 also also ADV cana-844 258 7 did do VERB cana-844 258 8 well well ADV cana-844 258 9 , , PUNCT cana-844 258 10 with with ADP cana-844 258 11 accuracies accuracy NOUN cana-844 258 12 of of ADP cana-844 258 13 93.93 93.93 NUM cana-844 258 14 % % NOUN cana-844 258 15 and and CCONJ cana-844 258 16 92.80 92.80 NUM cana-844 258 17 % % NOUN cana-844 258 18 respectively respectively ADV cana-844 258 19 . . PUNCT cana-844 259 1 logistic logistic ADJ cana-844 259 2 regression regression NOUN cana-844 259 3 had have VERB cana-844 259 4 a a DET cana-844 259 5 slightly slightly ADV cana-844 259 6 lower low ADJ cana-844 259 7 accuracy accuracy NOUN cana-844 259 8 of of ADP cana-844 259 9 90.41 90.41 NUM cana-844 259 10 % % NOUN cana-844 259 11 but but CCONJ cana-844 259 12 still still ADV cana-844 259 13 demonstrated demonstrate VERB cana-844 259 14 good good ADJ cana-844 259 15 predictive predictive ADJ cana-844 259 16 ability ability NOUN cana-844 259 17 . . PUNCT cana-844 260 1 fig fig NOUN cana-844 260 2 6 6 NUM cana-844 260 3 displays display VERB cana-844 260 4 the the DET cana-844 260 5 graphical graphical ADJ cana-844 260 6 representation representation NOUN cana-844 260 7 of of ADP cana-844 260 8 the the DET cana-844 260 9 accuracy accuracy NOUN cana-844 260 10 of of ADP cana-844 260 11 each each DET cana-844 260 12 model model NOUN cana-844 260 13 utilizing utilize VERB cana-844 260 14 vgg19 vgg19 PRON cana-844 260 15 . . PUNCT cana-844 261 1 the the DET cana-844 261 2 results result NOUN cana-844 261 3 highlight highlight VERB cana-844 261 4 how how SCONJ cana-844 261 5 different different ADJ cana-844 261 6 algorithms algorithm NOUN cana-844 261 7 can can AUX cana-844 261 8 accurately accurately ADV cana-844 261 9 predict predict VERB cana-844 261 10 results result NOUN cana-844 261 11 using use VERB cana-844 261 12 vgg19 vgg19 PROPN cana-844 261 13 features feature NOUN cana-844 261 14 , , PUNCT cana-844 261 15 providing provide VERB cana-844 261 16 useful useful ADJ cana-844 261 17 information information NOUN cana-844 261 18 for for ADP cana-844 261 19 improving improve VERB cana-844 261 20 models model NOUN cana-844 261 21 in in ADP cana-844 261 22 the the DET cana-844 261 23 future future NOUN cana-844 261 24 . . PUNCT cana-844 262 1 communications communication NOUN cana-844 262 2 on on ADP cana-844 262 3 applied apply VERB cana-844 262 4 nonlinear nonlinear ADJ cana-844 262 5 analysis analysis NOUN cana-844 262 6 issn issn NOUN cana-844 262 7 : : PUNCT cana-844 262 8 1074 1074 NUM cana-844 262 9 - - PUNCT cana-844 262 10 133x 133x NUM cana-844 262 11 vol vol NOUN cana-844 262 12 31 31 NUM cana-844 262 13 no no NOUN cana-844 262 14 . . PUNCT cana-844 263 1 4s 4s NUM cana-844 263 2 ( ( PUNCT cana-844 263 3 2024 2024 NUM cana-844 263 4 ) ) PUNCT cana-844 263 5 243 243 NUM cana-844 263 6 https://internationalpubls.com https://internationalpubls.com X cana-844 263 7 fig fig NOUN cana-844 263 8 6 6 NUM cana-844 263 9 : : PUNCT cana-844 263 10 graphical graphical ADJ cana-844 263 11 representation representation NOUN cana-844 263 12 of of ADP cana-844 263 13 the the DET cana-844 263 14 accuracy accuracy NOUN cana-844 263 15 of of ADP cana-844 263 16 each each DET cana-844 263 17 model model NOUN cana-844 263 18 utilizing utilize VERB cana-844 263 19 vgg19 vgg19 PROPN cana-844 263 20 analysis analysis NOUN cana-844 263 21 of of ADP cana-844 263 22 algorithmic algorithmic ADJ cana-844 263 23 performance performance NOUN cana-844 263 24 based base VERB cana-844 263 25 on on ADP cana-844 263 26 error error NOUN cana-844 263 27 rates rate NOUN cana-844 263 28 shows show VERB cana-844 263 29 different different ADJ cana-844 263 30 results result NOUN cana-844 263 31 for for ADP cana-844 263 32 each each DET cana-844 263 33 model model NOUN cana-844 263 34 using use VERB cana-844 263 35 vgg19 vgg19 PROPN cana-844 263 36 features feature NOUN cana-844 263 37 . . PUNCT cana-844 264 1 similarly similarly ADV cana-844 264 2 , , PUNCT cana-844 264 3 fig fig NOUN cana-844 264 4 7 7 NUM cana-844 264 5 displays display VERB cana-844 264 6 the the DET cana-844 264 7 graphical graphical ADJ cana-844 264 8 representation representation NOUN cana-844 264 9 of of ADP cana-844 264 10 the the DET cana-844 264 11 error error NOUN cana-844 264 12 rate rate NOUN cana-844 264 13 of of ADP cana-844 264 14 each each DET cana-844 264 15 model model NOUN cana-844 264 16 utilizing utilize VERB cana-844 264 17 vgg19 vgg19 PROPN cana-844 264 18 . . PUNCT cana-844 265 1 fig fig PROPN cana-844 265 2 7 7 NUM cana-844 265 3 : : PUNCT cana-844 265 4 graphical graphical ADJ cana-844 265 5 representation representation NOUN cana-844 265 6 of of ADP cana-844 265 7 the the DET cana-844 265 8 error error NOUN cana-844 265 9 rate rate NOUN cana-844 265 10 of of ADP cana-844 265 11 each each DET cana-844 265 12 model model NOUN cana-844 265 13 utilizing utilize VERB cana-844 265 14 vgg19 vgg19 NOUN cana-844 265 15 among among ADP cana-844 265 16 them they PRON cana-844 265 17 , , PUNCT cana-844 265 18 sequential_predictions_vgg19 sequential_predictions_vgg19 PROPN cana-844 265 19 stands stand VERB cana-844 265 20 out out ADP cana-844 265 21 as as ADP cana-844 265 22 the the DET cana-844 265 23 most most ADV cana-844 265 24 effective effective ADJ cana-844 265 25 algorithm algorithm NOUN cana-844 265 26 with with ADP cana-844 265 27 the the DET cana-844 265 28 lowest low ADJ cana-844 265 29 error error NOUN cana-844 265 30 rate rate NOUN cana-844 265 31 of of ADP cana-844 265 32 4.70 4.70 NUM cana-844 265 33 % % NOUN cana-844 265 34 , , PUNCT cana-844 265 35 showcasing showcase VERB cana-844 265 36 its its PRON cana-844 265 37 superior superior ADJ cana-844 265 38 predictive predictive ADJ cana-844 265 39 accuracy accuracy NOUN cana-844 265 40 . . PUNCT cana-844 266 1 following follow VERB cana-844 266 2 closely closely ADV cana-844 266 3 is be AUX cana-844 266 4 communications communication NOUN cana-844 266 5 on on ADP cana-844 266 6 applied apply VERB cana-844 266 7 nonlinear nonlinear ADJ cana-844 266 8 analysis analysis NOUN cana-844 266 9 issn issn NOUN cana-844 266 10 : : PUNCT cana-844 266 11 1074 1074 NUM cana-844 266 12 - - PUNCT cana-844 266 13 133x 133x NUM cana-844 266 14 vol vol NOUN cana-844 266 15 31 31 NUM cana-844 266 16 no no NOUN cana-844 266 17 . . PUNCT cana-844 267 1 4s 4s NUM cana-844 267 2 ( ( PUNCT cana-844 267 3 2024 2024 NUM cana-844 267 4 ) ) PUNCT cana-844 267 5 244 244 NUM cana-844 267 6 https://internationalpubls.com https://internationalpubls.com X cana-844 267 7 rfc_predictions_vgg19 rfc_predictions_vgg19 PROPN cana-844 267 8 , , PUNCT cana-844 267 9 which which PRON cana-844 267 10 demonstrates demonstrate VERB cana-844 267 11 a a DET cana-844 267 12 competitive competitive ADJ cana-844 267 13 error error NOUN cana-844 267 14 rate rate NOUN cana-844 267 15 of of ADP cana-844 267 16 5.41 5.41 NUM cana-844 267 17 % % NOUN cana-844 267 18 , , PUNCT cana-844 267 19 indicating indicate VERB cana-844 267 20 strong strong ADJ cana-844 267 21 performance performance NOUN cana-844 267 22 in in ADP cana-844 267 23 predictive predictive ADJ cana-844 267 24 modelling modelling NOUN cana-844 267 25 . . PUNCT cana-844 268 1 gbn_predictions_vgg19 gbn_predictions_vgg19 PROPN cana-844 268 2 displays display VERB cana-844 268 3 a a DET cana-844 268 4 moderate moderate ADJ cana-844 268 5 error error NOUN cana-844 268 6 rate rate NOUN cana-844 268 7 of of ADP cana-844 268 8 6.07 6.07 NUM cana-844 268 9 % % NOUN cana-844 268 10 , , PUNCT cana-844 268 11 showing show VERB cana-844 268 12 consistent consistent ADJ cana-844 268 13 performance performance NOUN cana-844 268 14 . . PUNCT cana-844 269 1 however however ADV cana-844 269 2 , , PUNCT cana-844 269 3 lr_predictions_vgg19 lr_predictions_vgg19 PROPN cana-844 269 4 and and CCONJ cana-844 269 5 knn_predictions_vgg19 knn_predictions_vgg19 PROPN cana-844 269 6 have have VERB cana-844 269 7 slightly slightly ADV cana-844 269 8 higher high ADJ cana-844 269 9 error error NOUN cana-844 269 10 rates rate NOUN cana-844 269 11 at at ADP cana-844 269 12 9.59 9.59 NUM cana-844 269 13 % % NOUN cana-844 269 14 and and CCONJ cana-844 269 15 7.20 7.20 NUM cana-844 269 16 % % NOUN cana-844 269 17 respectively respectively ADV cana-844 269 18 , , PUNCT cana-844 269 19 suggesting suggest VERB cana-844 269 20 less less ADJ cana-844 269 21 precision precision NOUN cana-844 269 22 in in ADP cana-844 269 23 their their PRON cana-844 269 24 predictions prediction NOUN cana-844 269 25 compared compare VERB cana-844 269 26 to to ADP cana-844 269 27 the the DET cana-844 269 28 other other ADJ cana-844 269 29 models model NOUN cana-844 269 30 . . PUNCT cana-844 270 1 similarly similarly ADV cana-844 270 2 , , PUNCT cana-844 270 3 fig fig NOUN cana-844 270 4 8 8 NUM cana-844 270 5 displays display VERB cana-844 270 6 the the DET cana-844 270 7 graphical graphical ADJ cana-844 270 8 representation representation NOUN cana-844 270 9 of of ADP cana-844 270 10 the the DET cana-844 270 11 precision precision NOUN cana-844 270 12 of of ADP cana-844 270 13 each each DET cana-844 270 14 model model NOUN cana-844 270 15 utilizing utilize VERB cana-844 270 16 vgg19 vgg19 PROPN cana-844 270 17 . . PUNCT cana-844 271 1 fig fig NOUN cana-844 271 2 8 8 NUM cana-844 271 3 : : PUNCT cana-844 271 4 graphical graphical ADJ cana-844 271 5 representation representation NOUN cana-844 271 6 of of ADP cana-844 271 7 the the DET cana-844 271 8 precision precision NOUN cana-844 271 9 of of ADP cana-844 271 10 each each DET cana-844 271 11 model model NOUN cana-844 271 12 utilizing utilize VERB cana-844 271 13 vgg19 vgg19 PROPN cana-844 271 14 fig fig NOUN cana-844 271 15 9 9 NUM cana-844 271 16 : : PUNCT cana-844 271 17 graphical graphical ADJ cana-844 271 18 representation representation NOUN cana-844 271 19 of of ADP cana-844 271 20 the the DET cana-844 271 21 recall recall NOUN cana-844 271 22 of of ADP cana-844 271 23 each each DET cana-844 271 24 model model NOUN cana-844 271 25 utilizing utilize VERB cana-844 271 26 vgg19 vgg19 PROPN cana-844 271 27 communications communication NOUN cana-844 271 28 on on ADP cana-844 271 29 applied apply VERB cana-844 271 30 nonlinear nonlinear ADJ cana-844 271 31 analysis analysis NOUN cana-844 271 32 issn issn NOUN cana-844 271 33 : : PUNCT cana-844 271 34 1074 1074 NUM cana-844 271 35 - - PUNCT cana-844 271 36 133x 133x NUM cana-844 271 37 vol vol NOUN cana-844 271 38 31 31 NUM cana-844 271 39 no no NOUN cana-844 271 40 . . PUNCT cana-844 272 1 4s 4s NUM cana-844 272 2 ( ( PUNCT cana-844 272 3 2024 2024 NUM cana-844 272 4 ) ) PUNCT cana-844 272 5 245 245 NUM cana-844 272 6 https://internationalpubls.com https://internationalpubls.com X cana-844 272 7 similarly similarly ADV cana-844 272 8 , , PUNCT cana-844 272 9 fig fig NOUN cana-844 272 10 9 9 NUM cana-844 272 11 displays display VERB cana-844 272 12 the the DET cana-844 272 13 graphical graphical ADJ cana-844 272 14 representation representation NOUN cana-844 272 15 of of ADP cana-844 272 16 the the DET cana-844 272 17 recall recall NOUN cana-844 272 18 of of ADP cana-844 272 19 each each DET cana-844 272 20 model model NOUN cana-844 272 21 utilizing utilize VERB cana-844 272 22 vgg19 vgg19 PRON cana-844 272 23 . . PUNCT cana-844 273 1 the the DET cana-844 273 2 random random ADJ cana-844 273 3 forest forest NOUN cana-844 273 4 classifier classifier NOUN cana-844 273 5 ( ( PUNCT cana-844 273 6 rfc rfc PROPN cana-844 273 7 ) ) PUNCT cana-844 273 8 performs perform VERB cana-844 273 9 the the DET cana-844 273 10 best good ADJ cana-844 273 11 in in ADP cana-844 273 12 terms term NOUN cana-844 273 13 of of ADP cana-844 273 14 precision precision NOUN cana-844 273 15 and and CCONJ cana-844 273 16 recall recall NOUN cana-844 273 17 among among ADP cana-844 273 18 all all DET cana-844 273 19 models model NOUN cana-844 273 20 , , PUNCT cana-844 273 21 showing show VERB cana-844 273 22 its its PRON cana-844 273 23 ability ability NOUN cana-844 273 24 to to PART cana-844 273 25 accurately accurately ADV cana-844 273 26 identify identify VERB cana-844 273 27 positive positive ADJ cana-844 273 28 samples sample NOUN cana-844 273 29 while while SCONJ cana-844 273 30 reducing reduce VERB cana-844 273 31 false false ADJ cana-844 273 32 positives positive NOUN cana-844 273 33 . . PUNCT cana-844 274 1 the the DET cana-844 274 2 sequential sequential ADJ cana-844 274 3 ann ann PROPN cana-844 274 4 model model NOUN cana-844 274 5 comes come VERB cana-844 274 6 next next ADV cana-844 274 7 after after ADP cana-844 274 8 rfc rfc NOUN cana-844 274 9 with with ADP cana-844 274 10 slightly slightly ADV cana-844 274 11 lower low ADJ cana-844 274 12 precision precision NOUN cana-844 274 13 and and CCONJ cana-844 274 14 recall recall NOUN cana-844 274 15 values value NOUN cana-844 274 16 , , PUNCT cana-844 274 17 indicating indicate VERB cana-844 274 18 similar similar ADJ cana-844 274 19 performance performance NOUN cana-844 274 20 in in ADP cana-844 274 21 classification classification NOUN cana-844 274 22 tasks task NOUN cana-844 274 23 . . PUNCT cana-844 275 1 the the DET cana-844 275 2 gaussian gaussian ADJ cana-844 275 3 naive naive ADJ cana-844 275 4 bayes bayes NOUN cana-844 275 5 ( ( PUNCT cana-844 275 6 gbn gbn NOUN cana-844 275 7 ) ) PUNCT cana-844 275 8 also also ADV cana-844 275 9 displays display VERB cana-844 275 10 high high ADJ cana-844 275 11 precision precision NOUN cana-844 275 12 and and CCONJ cana-844 275 13 recall recall NOUN cana-844 275 14 rates rate NOUN cana-844 275 15 , , PUNCT cana-844 275 16 showing show VERB cana-844 275 17 its its PRON cana-844 275 18 effectiveness effectiveness NOUN cana-844 275 19 in in ADP cana-844 275 20 correctly correctly ADV cana-844 275 21 classifying classify VERB cana-844 275 22 positive positive ADJ cana-844 275 23 samples sample NOUN cana-844 275 24 . . PUNCT cana-844 276 1 the the DET cana-844 276 2 k k NOUN cana-844 276 3 - - PUNCT cana-844 276 4 nearest near ADJ cana-844 276 5 neighbours neighbour NOUN cana-844 276 6 ( ( PUNCT cana-844 276 7 knn knn PROPN cana-844 276 8 ) ) PUNCT cana-844 276 9 model model NOUN cana-844 276 10 exhibits exhibit VERB cana-844 276 11 decent decent ADJ cana-844 276 12 precision precision NOUN cana-844 276 13 and and CCONJ cana-844 276 14 recall recall NOUN cana-844 276 15 values value NOUN cana-844 276 16 , , PUNCT cana-844 276 17 although although SCONJ cana-844 276 18 slightly slightly ADV cana-844 276 19 lower low ADJ cana-844 276 20 than than ADP cana-844 276 21 rfc rfc PROPN cana-844 276 22 , , PUNCT cana-844 276 23 ann ann PROPN cana-844 276 24 model model NOUN cana-844 276 25 , , PUNCT cana-844 276 26 and and CCONJ cana-844 276 27 gbn gbn NOUN cana-844 276 28 . . PUNCT cana-844 277 1 lastly lastly ADV cana-844 277 2 , , PUNCT cana-844 277 3 the the DET cana-844 277 4 logistic logistic ADJ cana-844 277 5 regression regression NOUN cana-844 277 6 ( ( PUNCT cana-844 277 7 lr lr NOUN cana-844 277 8 ) ) PUNCT cana-844 277 9 model model NOUN cana-844 277 10 shows show VERB cana-844 277 11 slightly slightly ADV cana-844 277 12 lower low ADJ cana-844 277 13 precision precision NOUN cana-844 277 14 and and CCONJ cana-844 277 15 recall recall NOUN cana-844 277 16 rates rate NOUN cana-844 277 17 compared compare VERB cana-844 277 18 to to ADP cana-844 277 19 other other ADJ cana-844 277 20 models model NOUN cana-844 277 21 , , PUNCT cana-844 277 22 suggesting suggest VERB cana-844 277 23 relatively relatively ADV cana-844 277 24 lower low ADJ cana-844 277 25 effectiveness effectiveness NOUN cana-844 277 26 in in ADP cana-844 277 27 classification classification NOUN cana-844 277 28 tasks task NOUN cana-844 277 29 . . PUNCT cana-844 278 1 the the DET cana-844 278 2 random random ADJ cana-844 278 3 forest forest NOUN cana-844 278 4 classifier classifier NOUN cana-844 278 5 ( ( PUNCT cana-844 278 6 rfc rfc PROPN cana-844 278 7 ) ) PUNCT cana-844 278 8 shows show VERB cana-844 278 9 the the DET cana-844 278 10 highest high ADJ cana-844 278 11 f1 f1 NOUN cana-844 278 12 - - PUNCT cana-844 278 13 score score NOUN cana-844 278 14 compared compare VERB cana-844 278 15 to to ADP cana-844 278 16 all all DET cana-844 278 17 models model NOUN cana-844 278 18 , , PUNCT cana-844 278 19 demonstrating demonstrate VERB cana-844 278 20 its its PRON cana-844 278 21 effectiveness effectiveness NOUN cana-844 278 22 in in ADP cana-844 278 23 balancing balance VERB cana-844 278 24 precision precision NOUN cana-844 278 25 and and CCONJ cana-844 278 26 recall recall NOUN cana-844 278 27 . . PUNCT cana-844 279 1 the the DET cana-844 279 2 sequential sequential ADJ cana-844 279 3 ann ann PROPN cana-844 279 4 model model NOUN cana-844 279 5 closely closely ADV cana-844 279 6 trails trail VERB cana-844 279 7 behind behind ADP cana-844 279 8 rfc rfc NOUN cana-844 279 9 with with ADP cana-844 279 10 a a DET cana-844 279 11 slightly slightly ADV cana-844 279 12 lower low ADJ cana-844 279 13 f1 f1 NOUN cana-844 279 14 - - PUNCT cana-844 279 15 score score NOUN cana-844 279 16 , , PUNCT cana-844 279 17 indicating indicate VERB cana-844 279 18 similar similar ADJ cana-844 279 19 performance performance NOUN cana-844 279 20 in in ADP cana-844 279 21 terms term NOUN cana-844 279 22 of of ADP cana-844 279 23 classification classification NOUN cana-844 279 24 accuracy accuracy NOUN cana-844 279 25 . . PUNCT cana-844 280 1 gaussian gaussian ADJ cana-844 280 2 naive naive ADJ cana-844 280 3 bayes bayes NOUN cana-844 280 4 ( ( PUNCT cana-844 280 5 gbn gbn NOUN cana-844 280 6 ) ) PUNCT cana-844 280 7 performs perform VERB cana-844 280 8 well well ADV cana-844 280 9 , , PUNCT cana-844 280 10 displaying display VERB cana-844 280 11 a a DET cana-844 280 12 high high ADJ cana-844 280 13 f1 f1 NOUN cana-844 280 14 - - PUNCT cana-844 280 15 score score NOUN cana-844 280 16 and and CCONJ cana-844 280 17 showcasing showcase VERB cana-844 280 18 its its PRON cana-844 280 19 ability ability NOUN cana-844 280 20 in in ADP cana-844 280 21 classification classification NOUN cana-844 280 22 tasks task NOUN cana-844 280 23 . . PUNCT cana-844 281 1 the the DET cana-844 281 2 k k NOUN cana-844 281 3 - - PUNCT cana-844 281 4 nearest near ADJ cana-844 281 5 neighbours neighbour NOUN cana-844 281 6 ( ( PUNCT cana-844 281 7 knn knn PROPN cana-844 281 8 ) ) PUNCT cana-844 281 9 model model NOUN cana-844 281 10 performs perform VERB cana-844 281 11 decently decently ADV cana-844 281 12 with with ADP cana-844 281 13 a a DET cana-844 281 14 respectable respectable ADJ cana-844 281 15 f1 f1 NOUN cana-844 281 16 - - PUNCT cana-844 281 17 score score NOUN cana-844 281 18 , , PUNCT cana-844 281 19 albeit albeit SCONJ cana-844 281 20 ranking rank VERB cana-844 281 21 lower low ADJ cana-844 281 22 than than ADP cana-844 281 23 rfc rfc PRON cana-844 281 24 , , PUNCT cana-844 281 25 sequential sequential ADJ cana-844 281 26 model model NOUN cana-844 281 27 , , PUNCT cana-844 281 28 and and CCONJ cana-844 281 29 gbn gbn NOUN cana-844 281 30 . . PUNCT cana-844 282 1 the the DET cana-844 282 2 logistic logistic ADJ cana-844 282 3 regression regression NOUN cana-844 282 4 ( ( PUNCT cana-844 282 5 lr lr NOUN cana-844 282 6 ) ) PUNCT cana-844 282 7 model model NOUN cana-844 282 8 exhibits exhibit VERB cana-844 282 9 the the DET cana-844 282 10 lowest low ADJ cana-844 282 11 f1 f1 NOUN cana-844 282 12 - - PUNCT cana-844 282 13 score score NOUN cana-844 282 14 among among ADP cana-844 282 15 the the DET cana-844 282 16 analysed analyse VERB cana-844 282 17 models model NOUN cana-844 282 18 , , PUNCT cana-844 282 19 showing show VERB cana-844 282 20 comparatively comparatively ADV cana-844 282 21 lower low ADJ cana-844 282 22 effectiveness effectiveness NOUN cana-844 282 23 in in ADP cana-844 282 24 classification classification NOUN cana-844 282 25 tasks task NOUN cana-844 282 26 . . PUNCT cana-844 283 1 the the DET cana-844 283 2 performance performance NOUN cana-844 283 3 gap gap NOUN cana-844 283 4 between between ADP cana-844 283 5 rfc rfc PROPN cana-844 283 6 , , PUNCT cana-844 283 7 sequential sequential ADJ cana-844 283 8 model model NOUN cana-844 283 9 , , PUNCT cana-844 283 10 and and CCONJ cana-844 283 11 gbn gbn NOUN cana-844 283 12 is be AUX cana-844 283 13 minimal minimal ADJ cana-844 283 14 , , PUNCT cana-844 283 15 implying imply VERB cana-844 283 16 that that SCONJ cana-844 283 17 any any PRON cana-844 283 18 of of ADP cana-844 283 19 these these DET cana-844 283 20 models model NOUN cana-844 283 21 could could AUX cana-844 283 22 be be AUX cana-844 283 23 selected select VERB cana-844 283 24 based base VERB cana-844 283 25 on on ADP cana-844 283 26 other other ADJ cana-844 283 27 factors factor NOUN cana-844 283 28 such such ADJ cana-844 283 29 as as ADP cana-844 283 30 computational computational ADJ cana-844 283 31 complexity complexity NOUN cana-844 283 32 , , PUNCT cana-844 283 33 interpretability interpretability NOUN cana-844 283 34 , , PUNCT cana-844 283 35 or or CCONJ cana-844 283 36 specific specific ADJ cana-844 283 37 task task NOUN cana-844 283 38 requirements requirement NOUN cana-844 283 39 . . PUNCT cana-844 284 1 fig fig NOUN cana-844 284 2 10 10 NUM cana-844 284 3 displays display VERB cana-844 284 4 the the DET cana-844 284 5 graphical graphical ADJ cana-844 284 6 representation representation NOUN cana-844 284 7 of of ADP cana-844 284 8 the the DET cana-844 284 9 f1 f1 NOUN cana-844 284 10 - - PUNCT cana-844 284 11 score score NOUN cana-844 284 12 of of ADP cana-844 284 13 each each DET cana-844 284 14 model model NOUN cana-844 284 15 utilizing utilize VERB cana-844 284 16 vgg19 vgg19 PROPN cana-844 284 17 . . PUNCT cana-844 285 1 fig fig NOUN cana-844 285 2 10 10 NUM cana-844 285 3 : : PUNCT cana-844 285 4 graphical graphical ADJ cana-844 285 5 representation representation NOUN cana-844 285 6 of of ADP cana-844 285 7 the the DET cana-844 285 8 f1 f1 NOUN cana-844 285 9 - - PUNCT cana-844 285 10 score score NOUN cana-844 285 11 of of ADP cana-844 285 12 each each DET cana-844 285 13 model model NOUN cana-844 285 14 utilizing utilize VERB cana-844 285 15 vgg19 vgg19 PROPN cana-844 285 16 communications communication NOUN cana-844 285 17 on on ADP cana-844 285 18 applied apply VERB cana-844 285 19 nonlinear nonlinear ADJ cana-844 285 20 analysis analysis NOUN cana-844 285 21 issn issn NOUN cana-844 285 22 : : PUNCT cana-844 285 23 1074 1074 NUM cana-844 285 24 - - PUNCT cana-844 285 25 133x 133x NUM cana-844 285 26 vol vol NOUN cana-844 285 27 31 31 NUM cana-844 285 28 no no NOUN cana-844 285 29 . . PUNCT cana-844 286 1 4s 4s NUM cana-844 286 2 ( ( PUNCT cana-844 286 3 2024 2024 NUM cana-844 286 4 ) ) PUNCT cana-844 286 5 246 246 NUM cana-844 286 6 https://internationalpubls.com https://internationalpubls.com X cana-844 286 7 the the DET cana-844 286 8 examination examination NOUN cana-844 286 9 of of ADP cana-844 286 10 results result NOUN cana-844 286 11 shows show VERB cana-844 286 12 significant significant ADJ cana-844 286 13 differences difference NOUN cana-844 286 14 in in ADP cana-844 286 15 training training NOUN cana-844 286 16 times time NOUN cana-844 286 17 among among ADP cana-844 286 18 various various ADJ cana-844 286 19 machine machine NOUN cana-844 286 20 learning learn VERB cana-844 286 21 algorithms algorithm NOUN cana-844 286 22 . . PUNCT cana-844 287 1 fig fig NOUN cana-844 287 2 11 11 NUM cana-844 287 3 displays display VERB cana-844 287 4 the the DET cana-844 287 5 graphical graphical ADJ cana-844 287 6 representation representation NOUN cana-844 287 7 of of ADP cana-844 287 8 the the DET cana-844 287 9 training training NOUN cana-844 287 10 time time NOUN cana-844 287 11 of of ADP cana-844 287 12 each each DET cana-844 287 13 model model NOUN cana-844 287 14 in in ADP cana-844 287 15 utilizing utilize VERB cana-844 287 16 vgg19 vgg19 PROPN cana-844 287 17 . . PUNCT cana-844 288 1 fig fig NOUN cana-844 288 2 11 11 NUM cana-844 288 3 : : PUNCT cana-844 289 1 graphical graphical ADJ cana-844 289 2 representation representation NOUN cana-844 289 3 of of ADP cana-844 289 4 the the DET cana-844 289 5 training training NOUN cana-844 289 6 time time NOUN cana-844 289 7 in in ADP cana-844 289 8 seconds second NOUN cana-844 289 9 for for ADP cana-844 289 10 each each DET cana-844 289 11 model model NOUN cana-844 289 12 utilizing utilize VERB cana-844 289 13 vgg19 vgg19 PROPN cana-844 289 14 k k ADV cana-844 289 15 - - PUNCT cana-844 289 16 nearest near ADJ cana-844 289 17 neighbours neighbour NOUN cana-844 289 18 ( ( PUNCT cana-844 289 19 knn knn PROPN cana-844 289 20 ) ) PUNCT cana-844 289 21 had have VERB cana-844 289 22 the the DET cana-844 289 23 shortest short ADJ cana-844 289 24 training training NOUN cana-844 289 25 time time NOUN cana-844 289 26 at at ADP cana-844 289 27 1 1 NUM cana-844 289 28 second second ADJ cana-844 289 29 , , PUNCT cana-844 289 30 highlighting highlight VERB cana-844 289 31 its its PRON cana-844 289 32 computational computational ADJ cana-844 289 33 efficiency efficiency NOUN cana-844 289 34 . . PUNCT cana-844 290 1 logistic logistic ADJ cana-844 290 2 regression regression NOUN cana-844 290 3 ( ( PUNCT cana-844 290 4 lr lr NOUN cana-844 290 5 ) ) PUNCT cana-844 290 6 followed follow VERB cana-844 290 7 with with ADP cana-844 290 8 a a DET cana-844 290 9 training training NOUN cana-844 290 10 time time NOUN cana-844 290 11 of of ADP cana-844 290 12 8 8 NUM cana-844 290 13 seconds second NOUN cana-844 290 14 , , PUNCT cana-844 290 15 indicating indicate VERB cana-844 290 16 its its PRON cana-844 290 17 suitability suitability NOUN cana-844 290 18 for for ADP cana-844 290 19 moderate moderate ADJ cana-844 290 20 - - PUNCT cana-844 290 21 scale scale NOUN cana-844 290 22 datasets dataset NOUN cana-844 290 23 . . PUNCT cana-844 291 1 gaussian gaussian ADJ cana-844 291 2 naΓ―ve naΓ―ve ADJ cana-844 291 3 bayes bayes PROPN cana-844 291 4 ( ( PUNCT cana-844 291 5 gbn gbn PROPN cana-844 291 6 ) ) PUNCT cana-844 291 7 had have VERB cana-844 291 8 a a DET cana-844 291 9 slightly slightly ADV cana-844 291 10 longer long ADJ cana-844 291 11 training training NOUN cana-844 291 12 time time NOUN cana-844 291 13 of of ADP cana-844 291 14 2 2 NUM cana-844 291 15 seconds second NOUN cana-844 291 16 , , PUNCT cana-844 291 17 showing show VERB cana-844 291 18 its its PRON cana-844 291 19 ability ability NOUN cana-844 291 20 to to PART cana-844 291 21 handle handle VERB cana-844 291 22 more more ADJ cana-844 291 23 complex complex ADJ cana-844 291 24 models model NOUN cana-844 291 25 than than ADP cana-844 291 26 lr lr PROPN cana-844 291 27 . . PROPN cana-844 291 28 random random ADJ cana-844 291 29 forest forest NOUN cana-844 291 30 classifier classifier NOUN cana-844 291 31 ( ( PUNCT cana-844 291 32 rfc rfc PROPN cana-844 291 33 ) ) PUNCT cana-844 291 34 had have VERB cana-844 291 35 a a DET cana-844 291 36 notably notably ADV cana-844 291 37 longer long ADJ cana-844 291 38 training training NOUN cana-844 291 39 time time NOUN cana-844 291 40 of of ADP cana-844 291 41 18 18 NUM cana-844 291 42 seconds second NOUN cana-844 291 43 , , PUNCT cana-844 291 44 possibly possibly ADV cana-844 291 45 due due ADP cana-844 291 46 to to ADP cana-844 291 47 its its PRON cana-844 291 48 ensemble ensemble ADJ cana-844 291 49 nature nature NOUN cana-844 291 50 and and CCONJ cana-844 291 51 complexity complexity NOUN cana-844 291 52 . . PUNCT cana-844 292 1 the the DET cana-844 292 2 sequential sequential ADJ cana-844 292 3 model model NOUN cana-844 292 4 had have VERB cana-844 292 5 the the DET cana-844 292 6 longest long ADJ cana-844 292 7 training training NOUN cana-844 292 8 time time NOUN cana-844 292 9 at at ADP cana-844 292 10 25 25 NUM cana-844 292 11 seconds second NOUN cana-844 292 12 , , PUNCT cana-844 292 13 likely likely ADJ cana-844 292 14 because because SCONJ cana-844 292 15 of of ADP cana-844 292 16 its its PRON cana-844 292 17 deep deep ADJ cana-844 292 18 learning learning NOUN cana-844 292 19 architecture architecture NOUN cana-844 292 20 , , PUNCT cana-844 292 21 which which PRON cana-844 292 22 typically typically ADV cana-844 292 23 requires require VERB cana-844 292 24 more more ADJ cana-844 292 25 computational computational ADJ cana-844 292 26 resources resource NOUN cana-844 292 27 and and CCONJ cana-844 292 28 time time NOUN cana-844 292 29 to to PART cana-844 292 30 converge converge VERB cana-844 292 31 . . PUNCT cana-844 293 1 5.2 5.2 NUM cana-844 293 2 resnet50 resnet50 NOUN cana-844 293 3 image image NOUN cana-844 293 4 classification classification NOUN cana-844 293 5 with with ADP cana-844 293 6 various various ADJ cana-844 293 7 classifiers classifier NOUN cana-844 293 8 the the DET cana-844 293 9 results result NOUN cana-844 293 10 from from ADP cana-844 293 11 the the DET cana-844 293 12 experiment experiment NOUN cana-844 293 13 on on ADP cana-844 293 14 image image NOUN cana-844 293 15 classification classification NOUN cana-844 293 16 using use VERB cana-844 293 17 the the DET cana-844 293 18 resnet50 resnet50 NOUN cana-844 293 19 model model NOUN cana-844 293 20 and and CCONJ cana-844 293 21 various various ADJ cana-844 293 22 classifiers classifier NOUN cana-844 293 23 indicate indicate VERB cana-844 293 24 significant significant ADJ cana-844 293 25 differences difference NOUN cana-844 293 26 in in ADP cana-844 293 27 accuracy accuracy NOUN cana-844 293 28 and and CCONJ cana-844 293 29 error error NOUN cana-844 293 30 rates rate NOUN cana-844 293 31 . . PUNCT cana-844 294 1 k k X cana-844 294 2 - - PUNCT cana-844 294 3 nearest near ADJ cana-844 294 4 neighbours neighbour NOUN cana-844 294 5 ( ( PUNCT cana-844 294 6 knn knn PROPN cana-844 294 7 ) ) PUNCT cana-844 294 8 achieved achieve VERB cana-844 294 9 93.9984 93.9984 NUM cana-844 294 10 % % NOUN cana-844 294 11 accuracy accuracy NOUN cana-844 294 12 with with ADP cana-844 294 13 a a DET cana-844 294 14 7.001975 7.001975 NUM cana-844 294 15 % % NOUN cana-844 294 16 error error NOUN cana-844 294 17 rate rate NOUN cana-844 294 18 , , PUNCT cana-844 294 19 showing show VERB cana-844 294 20 good good ADJ cana-844 294 21 performance performance NOUN cana-844 294 22 with with ADP cana-844 294 23 a a DET cana-844 294 24 slightly slightly ADV cana-844 294 25 higher high ADJ cana-844 294 26 error error NOUN cana-844 294 27 margin margin NOUN cana-844 294 28 . . PUNCT cana-844 295 1 logistic logistic ADJ cana-844 295 2 regression regression NOUN cana-844 295 3 ( ( PUNCT cana-844 295 4 lr lr NOUN cana-844 295 5 ) ) PUNCT cana-844 295 6 had have VERB cana-844 295 7 lower low ADJ cana-844 295 8 accuracy accuracy NOUN cana-844 295 9 at at ADP cana-844 295 10 91.2526 91.2526 NUM cana-844 295 11 % % NOUN cana-844 295 12 and and CCONJ cana-844 295 13 a a DET cana-844 295 14 higher high ADJ cana-844 295 15 error error NOUN cana-844 295 16 rate rate NOUN cana-844 295 17 of of ADP cana-844 295 18 8.78475 8.78475 NUM cana-844 295 19 % % NOUN cana-844 295 20 . . PUNCT cana-844 296 1 gaussian gaussian ADJ cana-844 296 2 naΓ―ve naΓ―ve ADJ cana-844 296 3 bayes bayes PROPN cana-844 296 4 ( ( PUNCT cana-844 296 5 gbn gbn PROPN cana-844 296 6 ) ) PUNCT cana-844 296 7 performed perform VERB cana-844 296 8 better well ADV cana-844 296 9 with with ADP cana-844 296 10 an an DET cana-844 296 11 accuracy accuracy NOUN cana-844 296 12 of of ADP cana-844 296 13 94.5636 94.5636 NUM cana-844 296 14 % % NOUN cana-844 296 15 and and CCONJ cana-844 296 16 a a DET cana-844 296 17 lower low ADJ cana-844 296 18 error error NOUN cana-844 296 19 rate rate NOUN cana-844 296 20 of of ADP cana-844 296 21 5.436399 5.436399 NUM cana-844 296 22 % % NOUN cana-844 296 23 , , PUNCT cana-844 296 24 suggesting suggest VERB cana-844 296 25 its its PRON cana-844 296 26 effectiveness effectiveness NOUN cana-844 296 27 in in ADP cana-844 296 28 improving improve VERB cana-844 296 29 predictions prediction NOUN cana-844 296 30 . . PUNCT cana-844 297 1 the the DET cana-844 297 2 rfc rfc NOUN cana-844 297 3 achieved achieve VERB cana-844 297 4 an an DET cana-844 297 5 accuracy accuracy NOUN cana-844 297 6 of of ADP cana-844 297 7 96.78082 96.78082 NUM cana-844 297 8 % % NOUN cana-844 297 9 and and CCONJ cana-844 297 10 an an DET cana-844 297 11 error error NOUN cana-844 297 12 rate rate NOUN cana-844 297 13 of of ADP cana-844 297 14 4.219178 4.219178 NUM cana-844 297 15 % % NOUN cana-844 297 16 , , PUNCT cana-844 297 17 demonstrating demonstrate VERB cana-844 297 18 its its PRON cana-844 297 19 effectiveness effectiveness NOUN cana-844 297 20 in in ADP cana-844 297 21 image image NOUN cana-844 297 22 classification classification NOUN cana-844 297 23 . . PUNCT cana-844 298 1 on on ADP cana-844 298 2 the the DET cana-844 298 3 other other ADJ cana-844 298 4 hand hand NOUN cana-844 298 5 , , PUNCT cana-844 298 6 the the DET cana-844 298 7 sequential sequential ADJ cana-844 298 8 model model NOUN cana-844 298 9 surpassed surpass VERB cana-844 298 10 all all DET cana-844 298 11 other other ADJ cana-844 298 12 classifiers classifier NOUN cana-844 298 13 by by ADP cana-844 298 14 achieving achieve VERB cana-844 298 15 the the DET cana-844 298 16 highest high ADJ cana-844 298 17 accuracy accuracy NOUN cana-844 298 18 of of ADP cana-844 298 19 98.84765 98.84765 NUM cana-844 298 20 % % NOUN cana-844 298 21 and and CCONJ cana-844 298 22 a a DET cana-844 298 23 minimal minimal ADJ cana-844 298 24 error error NOUN cana-844 298 25 rate rate NOUN cana-844 298 26 of of ADP cana-844 298 27 2.152641879 2.152641879 NUM cana-844 298 28 % % NOUN cana-844 298 29 . . PUNCT cana-844 299 1 communications communication NOUN cana-844 299 2 on on ADP cana-844 299 3 applied apply VERB cana-844 299 4 nonlinear nonlinear ADJ cana-844 299 5 analysis analysis NOUN cana-844 299 6 issn issn NOUN cana-844 299 7 : : PUNCT cana-844 299 8 1074 1074 NUM cana-844 299 9 - - PUNCT cana-844 299 10 133x 133x NUM cana-844 299 11 vol vol NOUN cana-844 299 12 31 31 NUM cana-844 299 13 no no NOUN cana-844 299 14 . . PUNCT cana-844 300 1 4s 4s NUM cana-844 300 2 ( ( PUNCT cana-844 300 3 2024 2024 NUM cana-844 300 4 ) ) PUNCT cana-844 300 5 247 247 NUM cana-844 300 6 https://internationalpubls.com https://internationalpubls.com X cana-844 300 7 this this PRON cana-844 300 8 highlights highlight VERB cana-844 300 9 its its PRON cana-844 300 10 superior superior ADJ cana-844 300 11 performance performance NOUN cana-844 300 12 in in ADP cana-844 300 13 image image NOUN cana-844 300 14 classification classification NOUN cana-844 300 15 tasks task NOUN cana-844 300 16 when when SCONJ cana-844 300 17 used use VERB cana-844 300 18 with with ADP cana-844 300 19 the the DET cana-844 300 20 resnet50 resnet50 NOUN cana-844 300 21 model model PROPN cana-844 300 22 . . PUNCT cana-844 301 1 fig fig NOUN cana-844 301 2 12 12 NUM cana-844 301 3 displays display VERB cana-844 301 4 the the DET cana-844 301 5 graphical graphical ADJ cana-844 301 6 representation representation NOUN cana-844 301 7 of of ADP cana-844 301 8 the the DET cana-844 301 9 accuracy accuracy NOUN cana-844 301 10 of of ADP cana-844 301 11 each each DET cana-844 301 12 model model NOUN cana-844 301 13 utilizingresnet50 utilizingresnet50 PROPN cana-844 301 14 . . PUNCT cana-844 302 1 fig fig NOUN cana-844 302 2 12 12 NUM cana-844 302 3 : : PUNCT cana-844 302 4 graphical graphical ADJ cana-844 302 5 representation representation NOUN cana-844 302 6 of of ADP cana-844 302 7 the the DET cana-844 302 8 accuracy accuracy NOUN cana-844 302 9 of of ADP cana-844 302 10 each each DET cana-844 302 11 model model NOUN cana-844 302 12 utilizing utilize VERB cana-844 302 13 resnet50 resnet50 NOUN cana-844 302 14 fig fig NOUN cana-844 302 15 13 13 NUM cana-844 302 16 displays display VERB cana-844 302 17 the the DET cana-844 302 18 graphical graphical ADJ cana-844 302 19 representation representation NOUN cana-844 302 20 of of ADP cana-844 302 21 the the DET cana-844 302 22 error error NOUN cana-844 302 23 rate rate NOUN cana-844 302 24 of of ADP cana-844 302 25 each each DET cana-844 302 26 model model NOUN cana-844 302 27 utilizing utilize VERB cana-844 302 28 resnet50 resnet50 NOUN cana-844 302 29 . . PUNCT cana-844 303 1 these these DET cana-844 303 2 findings finding NOUN cana-844 303 3 emphasize emphasize VERB cana-844 303 4 the the DET cana-844 303 5 importance importance NOUN cana-844 303 6 of of ADP cana-844 303 7 choosing choose VERB cana-844 303 8 the the DET cana-844 303 9 right right ADJ cana-844 303 10 classifiers classifier NOUN cana-844 303 11 to to PART cana-844 303 12 improve improve VERB cana-844 303 13 accuracy accuracy NOUN cana-844 303 14 and and CCONJ cana-844 303 15 minimize minimize VERB cana-844 303 16 errors error NOUN cana-844 303 17 in in ADP cana-844 303 18 image image NOUN cana-844 303 19 classification classification NOUN cana-844 303 20 applications application NOUN cana-844 303 21 . . PUNCT cana-844 304 1 fig fig NOUN cana-844 304 2 13 13 NUM cana-844 304 3 : : PUNCT cana-844 304 4 graphical graphical ADJ cana-844 304 5 representation representation NOUN cana-844 304 6 of of ADP cana-844 304 7 the the DET cana-844 304 8 error error NOUN cana-844 304 9 rate rate NOUN cana-844 304 10 of of ADP cana-844 304 11 each each DET cana-844 304 12 model model NOUN cana-844 304 13 utilizing utilize VERB cana-844 304 14 resnet50 resnet50 NOUN cana-844 304 15 communications communication NOUN cana-844 304 16 on on ADP cana-844 304 17 applied apply VERB cana-844 304 18 nonlinear nonlinear ADJ cana-844 304 19 analysis analysis NOUN cana-844 304 20 issn issn NOUN cana-844 304 21 : : PUNCT cana-844 304 22 1074 1074 NUM cana-844 304 23 - - PUNCT cana-844 304 24 133x 133x NUM cana-844 304 25 vol vol NOUN cana-844 304 26 31 31 NUM cana-844 304 27 no no NOUN cana-844 304 28 . . PUNCT cana-844 305 1 4s 4s NUM cana-844 305 2 ( ( PUNCT cana-844 305 3 2024 2024 NUM cana-844 305 4 ) ) PUNCT cana-844 305 5 248 248 NUM cana-844 305 6 https://internationalpubls.com https://internationalpubls.com X cana-844 305 7 the the DET cana-844 305 8 examination examination NOUN cana-844 305 9 of of ADP cana-844 305 10 outcomes outcome NOUN cana-844 305 11 from from ADP cana-844 305 12 the the DET cana-844 305 13 resnet50 resnet50 NOUN cana-844 305 14 model model NOUN cana-844 305 15 using use VERB cana-844 305 16 different different ADJ cana-844 305 17 classifiers classifier NOUN cana-844 305 18 , , PUNCT cana-844 305 19 with with ADP cana-844 305 20 a a DET cana-844 305 21 focus focus NOUN cana-844 305 22 on on ADP cana-844 305 23 precision precision NOUN cana-844 305 24 and and CCONJ cana-844 305 25 recall recall NOUN cana-844 305 26 metrics metric NOUN cana-844 305 27 , , PUNCT cana-844 305 28 provides provide VERB cana-844 305 29 valuable valuable ADJ cana-844 305 30 insights insight NOUN cana-844 305 31 into into ADP cana-844 305 32 how how SCONJ cana-844 305 33 well well ADV cana-844 305 34 each each DET cana-844 305 35 classifier classifier NOUN cana-844 305 36 performs perform VERB cana-844 305 37 in in ADP cana-844 305 38 image image NOUN cana-844 305 39 classification classification NOUN cana-844 305 40 tasks task NOUN cana-844 305 41 . . PUNCT cana-844 306 1 fig fig NOUN cana-844 306 2 14 14 NUM cana-844 306 3 displays display VERB cana-844 306 4 the the DET cana-844 306 5 graphical graphical ADJ cana-844 306 6 representation representation NOUN cana-844 306 7 of of ADP cana-844 306 8 the the DET cana-844 306 9 precision precision NOUN cana-844 306 10 of of ADP cana-844 306 11 each each DET cana-844 306 12 model model NOUN cana-844 306 13 utilizingresnet50 utilizingresnet50 PROPN cana-844 306 14 . . PUNCT cana-844 307 1 fig fig NOUN cana-844 307 2 14 14 NUM cana-844 307 3 : : PUNCT cana-844 307 4 graphical graphical ADJ cana-844 307 5 representation representation NOUN cana-844 307 6 of of ADP cana-844 307 7 the the DET cana-844 307 8 precision precision NOUN cana-844 307 9 of of ADP cana-844 307 10 each each DET cana-844 307 11 model model NOUN cana-844 307 12 utilizing utilize VERB cana-844 307 13 resnet50 resnet50 NOUN cana-844 307 14 fig fig NOUN cana-844 307 15 15 15 NUM cana-844 307 16 : : PUNCT cana-844 307 17 graphical graphical ADJ cana-844 307 18 representation representation NOUN cana-844 307 19 of of ADP cana-844 307 20 the the DET cana-844 307 21 recall recall NOUN cana-844 307 22 of of ADP cana-844 307 23 each each DET cana-844 307 24 model model NOUN cana-844 307 25 utilizing utilize VERB cana-844 307 26 resnet50 resnet50 NOUN cana-844 307 27 communications communication NOUN cana-844 307 28 on on ADP cana-844 307 29 applied apply VERB cana-844 307 30 nonlinear nonlinear ADJ cana-844 307 31 analysis analysis NOUN cana-844 307 32 issn issn NOUN cana-844 307 33 : : PUNCT cana-844 307 34 1074 1074 NUM cana-844 307 35 - - PUNCT cana-844 307 36 133x 133x NUM cana-844 307 37 vol vol NOUN cana-844 307 38 31 31 NUM cana-844 307 39 no no NOUN cana-844 307 40 . . PUNCT cana-844 308 1 4s 4s NUM cana-844 308 2 ( ( PUNCT cana-844 308 3 2024 2024 NUM cana-844 308 4 ) ) PUNCT cana-844 308 5 249 249 NUM cana-844 308 6 https://internationalpubls.com https://internationalpubls.com X cana-844 308 7 fig fig NOUN cana-844 308 8 15 15 NUM cana-844 308 9 displays display VERB cana-844 308 10 the the DET cana-844 308 11 graphical graphical ADJ cana-844 308 12 representation representation NOUN cana-844 308 13 of of ADP cana-844 308 14 the the DET cana-844 308 15 recall recall NOUN cana-844 308 16 of of ADP cana-844 308 17 each each DET cana-844 308 18 model model NOUN cana-844 308 19 utilizingresnet50 utilizingresnet50 PROPN cana-844 308 20 . . PUNCT cana-844 309 1 knearest knearest PROPN cana-844 309 2 neighbors neighbor NOUN cana-844 309 3 ( ( PUNCT cana-844 309 4 knn knn PROPN cana-844 309 5 ) ) PUNCT cana-844 309 6 demonstrated demonstrate VERB cana-844 309 7 a a DET cana-844 309 8 precision precision NOUN cana-844 309 9 rate rate NOUN cana-844 309 10 of of ADP cana-844 309 11 93.27631 93.27631 NUM cana-844 309 12 % % NOUN cana-844 309 13 and and CCONJ cana-844 309 14 a a DET cana-844 309 15 recall recall NOUN cana-844 309 16 rate rate NOUN cana-844 309 17 of of ADP cana-844 309 18 93.99804 93.99804 NUM cana-844 309 19 % % NOUN cana-844 309 20 , , PUNCT cana-844 309 21 indicating indicate VERB cana-844 309 22 its its PRON cana-844 309 23 capacity capacity NOUN cana-844 309 24 to to PART cana-844 309 25 accurately accurately ADV cana-844 309 26 classify classify VERB cana-844 309 27 images image NOUN cana-844 309 28 while while SCONJ cana-844 309 29 upholding uphold VERB cana-844 309 30 a a DET cana-844 309 31 high high ADJ cana-844 309 32 precision precision NOUN cana-844 309 33 in in ADP cana-844 309 34 recognizing recognize VERB cana-844 309 35 pertinent pertinent ADJ cana-844 309 36 instances instance NOUN cana-844 309 37 . . PUNCT cana-844 310 1 conversely conversely ADV cana-844 310 2 , , PUNCT cana-844 310 3 logistic logistic ADJ cana-844 310 4 regression regression NOUN cana-844 310 5 ( ( PUNCT cana-844 310 6 lr lr NOUN cana-844 310 7 ) ) PUNCT cana-844 310 8 exhibited exhibit VERB cana-844 310 9 a a DET cana-844 310 10 slightly slightly ADV cana-844 310 11 lower low ADJ cana-844 310 12 precision precision NOUN cana-844 310 13 rate rate NOUN cana-844 310 14 of of ADP cana-844 310 15 91.65832226 91.65832226 NUM cana-844 310 16 % % NOUN cana-844 310 17 and and CCONJ cana-844 310 18 a a DET cana-844 310 19 recall recall NOUN cana-844 310 20 rate rate NOUN cana-844 310 21 of of ADP cana-844 310 22 90.21526419 90.21526419 NUM cana-844 310 23 % % NOUN cana-844 310 24 , , PUNCT cana-844 310 25 implying imply VERB cana-844 310 26 a a DET cana-844 310 27 moderate moderate ADJ cana-844 310 28 performance performance NOUN cana-844 310 29 in in ADP cana-844 310 30 accurately accurately ADV cana-844 310 31 identifying identify VERB cana-844 310 32 relevant relevant ADJ cana-844 310 33 instances instance NOUN cana-844 310 34 and and CCONJ cana-844 310 35 reducing reduce VERB cana-844 310 36 false false ADJ cana-844 310 37 positives positive NOUN cana-844 310 38 . . PUNCT cana-844 311 1 naive naive ADJ cana-844 311 2 bayes bayes PROPN cana-844 311 3 demonstrated demonstrate VERB cana-844 311 4 enhanced enhanced ADJ cana-844 311 5 recall recall NOUN cana-844 311 6 ( ( PUNCT cana-844 311 7 94.5636 94.5636 NUM cana-844 311 8 % % NOUN cana-844 311 9 ) ) PUNCT cana-844 311 10 and and CCONJ cana-844 311 11 precision precision NOUN cana-844 311 12 ( ( PUNCT cana-844 311 13 94.81437 94.81437 NUM cana-844 311 14 % % NOUN cana-844 311 15 ) ) PUNCT cana-844 311 16 , , PUNCT cana-844 311 17 demonstrating demonstrate VERB cana-844 311 18 its its PRON cana-844 311 19 efficacy efficacy NOUN cana-844 311 20 in in ADP cana-844 311 21 correctly correctly ADV cana-844 311 22 identifying identify VERB cana-844 311 23 cases case NOUN cana-844 311 24 while while SCONJ cana-844 311 25 reducing reduce VERB cana-844 311 26 false false ADJ cana-844 311 27 negatives negative NOUN cana-844 311 28 . . PUNCT cana-844 312 1 with with ADP cana-844 312 2 greater great ADJ cana-844 312 3 precision precision NOUN cana-844 312 4 and and CCONJ cana-844 312 5 recall recall NOUN cana-844 312 6 values value NOUN cana-844 312 7 of of ADP cana-844 312 8 95.97739 95.97739 NUM cana-844 312 9 % % NOUN cana-844 312 10 and and CCONJ cana-844 312 11 96.78082 96.78082 NUM cana-844 312 12 % % NOUN cana-844 312 13 , , PUNCT cana-844 312 14 respectively respectively ADV cana-844 312 15 , , PUNCT cana-844 312 16 the the DET cana-844 312 17 random random ADJ cana-844 312 18 forest forest NOUN cana-844 312 19 classifier classifier NOUN cana-844 312 20 ( ( PUNCT cana-844 312 21 rfc rfc PROPN cana-844 312 22 ) ) PUNCT cana-844 312 23 proved prove VERB cana-844 312 24 its its PRON cana-844 312 25 capacity capacity NOUN cana-844 312 26 to to PART cana-844 312 27 precisely precisely ADV cana-844 312 28 group group NOUN cana-844 312 29 instances instance NOUN cana-844 312 30 and and CCONJ cana-844 312 31 retrieve retrieve VERB cana-844 312 32 pertinent pertinent ADJ cana-844 312 33 examples example NOUN cana-844 312 34 from from ADP cana-844 312 35 the the DET cana-844 312 36 dataset dataset NOUN cana-844 312 37 . . PUNCT cana-844 313 1 with with ADP cana-844 313 2 a a DET cana-844 313 3 maximum maximum ADJ cana-844 313 4 precision precision NOUN cana-844 313 5 of of ADP cana-844 313 6 97.93441349 97.93441349 NUM cana-844 313 7 % % NOUN cana-844 313 8 and and CCONJ cana-844 313 9 a a DET cana-844 313 10 recall recall NOUN cana-844 313 11 of of ADP cana-844 313 12 98.84765 98.84765 NUM cana-844 313 13 % % NOUN cana-844 313 14 , , PUNCT cana-844 313 15 the the DET cana-844 313 16 sequential sequential ADJ cana-844 313 17 model model NOUN cana-844 313 18 surpassed surpass VERB cana-844 313 19 the the DET cana-844 313 20 rest rest NOUN cana-844 313 21 of of ADP cana-844 313 22 the the DET cana-844 313 23 classifiers classifier NOUN cana-844 313 24 , , PUNCT cana-844 313 25 demonstrating demonstrate VERB cana-844 313 26 its its PRON cana-844 313 27 greater great ADJ cana-844 313 28 proficiency proficiency NOUN cana-844 313 29 in in ADP cana-844 313 30 correctly correctly ADV cana-844 313 31 detecting detect VERB cana-844 313 32 meaningful meaningful ADJ cana-844 313 33 instances instance NOUN cana-844 313 34 and and CCONJ cana-844 313 35 minimising minimise VERB cana-844 313 36 false false ADJ cana-844 313 37 positives positive NOUN cana-844 313 38 and and CCONJ cana-844 313 39 negatives negative NOUN cana-844 313 40 . . PUNCT cana-844 314 1 the the DET cana-844 314 2 significance significance NOUN cana-844 314 3 of of ADP cana-844 314 4 recall recall NOUN cana-844 314 5 and and CCONJ cana-844 314 6 precision precision NOUN cana-844 314 7 metrics metric NOUN cana-844 314 8 in in ADP cana-844 314 9 assessing assess VERB cana-844 314 10 the the DET cana-844 314 11 effectiveness effectiveness NOUN cana-844 314 12 of of ADP cana-844 314 13 classifiers classifier NOUN cana-844 314 14 for for ADP cana-844 314 15 tasks task NOUN cana-844 314 16 such such ADJ cana-844 314 17 as as SCONJ cana-844 314 18 image image NOUN cana-844 314 19 classification classification NOUN cana-844 314 20 is be AUX cana-844 314 21 highlighted highlight VERB cana-844 314 22 by by ADP cana-844 314 23 these these DET cana-844 314 24 findings finding NOUN cana-844 314 25 , , PUNCT cana-844 314 26 which which PRON cana-844 314 27 provide provide VERB cana-844 314 28 well well ADV cana-844 314 29 - - PUNCT cana-844 314 30 informed inform VERB cana-844 314 31 selection selection NOUN cana-844 314 32 according accord VERB cana-844 314 33 to to ADP cana-844 314 34 particular particular ADJ cana-844 314 35 requirements requirement NOUN cana-844 314 36 and and CCONJ cana-844 314 37 limitations limitation NOUN cana-844 314 38 . . PUNCT cana-844 315 1 when when SCONJ cana-844 315 2 analysing analyse VERB cana-844 315 3 the the DET cana-844 315 4 results result NOUN cana-844 315 5 , , PUNCT cana-844 315 6 the the DET cana-844 315 7 f1 f1 NOUN cana-844 315 8 score score NOUN cana-844 315 9 is be AUX cana-844 315 10 a a DET cana-844 315 11 crucial crucial ADJ cana-844 315 12 metric metric NOUN cana-844 315 13 for for ADP cana-844 315 14 evaluating evaluate VERB cana-844 315 15 how how SCONJ cana-844 315 16 well well ADV cana-844 315 17 different different ADJ cana-844 315 18 models model NOUN cana-844 315 19 perform perform VERB cana-844 315 20 in in ADP cana-844 315 21 image image NOUN cana-844 315 22 classification classification NOUN cana-844 315 23 using use VERB cana-844 315 24 the the DET cana-844 315 25 resnet50 resnet50 NOUN cana-844 315 26 architecture architecture NOUN cana-844 315 27 . . PUNCT cana-844 316 1 fig fig NOUN cana-844 316 2 16 16 NUM cana-844 316 3 displays display VERB cana-844 316 4 the the DET cana-844 316 5 graphical graphical ADJ cana-844 316 6 representation representation NOUN cana-844 316 7 f1 f1 NOUN cana-844 316 8 - - PUNCT cana-844 316 9 score score NOUN cana-844 316 10 of of ADP cana-844 316 11 each each DET cana-844 316 12 model model NOUN cana-844 316 13 utilizing utilize VERB cana-844 316 14 resnet50 resnet50 NOUN cana-844 316 15 . . PUNCT cana-844 317 1 fig fig NOUN cana-844 317 2 16 16 NUM cana-844 317 3 : : PUNCT cana-844 317 4 graphical graphical ADJ cana-844 317 5 representation representation NOUN cana-844 317 6 of of ADP cana-844 317 7 the the DET cana-844 317 8 f1 f1 NOUN cana-844 317 9 - - PUNCT cana-844 317 10 score score NOUN cana-844 317 11 of of ADP cana-844 317 12 each each DET cana-844 317 13 model model NOUN cana-844 317 14 utilizing utilize VERB cana-844 317 15 resnet50 resnet50 NOUN cana-844 317 16 the the DET cana-844 317 17 sequential sequential ADJ cana-844 317 18 ann ann PROPN cana-844 317 19 model model NOUN cana-844 317 20 stands stand VERB cana-844 317 21 out out ADP cana-844 317 22 with with ADP cana-844 317 23 the the DET cana-844 317 24 highest high ADJ cana-844 317 25 f1 f1 ADJ cana-844 317 26 score score NOUN cana-844 317 27 of of ADP cana-844 317 28 98.84536 98.84536 NUM cana-844 317 29 % % NOUN cana-844 317 30 among among ADP cana-844 317 31 the the DET cana-844 317 32 models model NOUN cana-844 317 33 assessed assess VERB cana-844 317 34 , , PUNCT cana-844 317 35 showing show VERB cana-844 317 36 a a DET cana-844 317 37 strong strong ADJ cana-844 317 38 balance balance NOUN cana-844 317 39 between between ADP cana-844 317 40 precision precision NOUN cana-844 317 41 and and CCONJ cana-844 317 42 recall recall NOUN cana-844 317 43 in in ADP cana-844 317 44 image image NOUN cana-844 317 45 classification classification NOUN cana-844 317 46 . . PUNCT cana-844 318 1 the the DET cana-844 318 2 random random ADJ cana-844 318 3 forest forest NOUN cana-844 318 4 classifier classifier NOUN cana-844 318 5 ( ( PUNCT cana-844 318 6 rfc rfc PROPN cana-844 318 7 ) ) PUNCT cana-844 318 8 follows follow VERB cana-844 318 9 closely closely ADV cana-844 318 10 behind behind ADV cana-844 318 11 with with ADP cana-844 318 12 an an DET cana-844 318 13 f1 f1 ADJ cana-844 318 14 score score NOUN cana-844 318 15 of of ADP cana-844 318 16 96.76431 96.76431 NUM cana-844 318 17 % % NOUN cana-844 318 18 , , PUNCT cana-844 318 19 indicating indicate VERB cana-844 318 20 reliable reliable ADJ cana-844 318 21 performance performance NOUN cana-844 318 22 in in ADP cana-844 318 23 identifying identify VERB cana-844 318 24 true true ADJ cana-844 318 25 positives positive NOUN cana-844 318 26 while while SCONJ cana-844 318 27 minimizing minimize VERB cana-844 318 28 false false ADJ cana-844 318 29 positives positive NOUN cana-844 318 30 and and CCONJ cana-844 318 31 false false ADJ cana-844 318 32 negatives negative NOUN cana-844 318 33 . . PUNCT cana-844 319 1 the the DET cana-844 319 2 gaussian gaussian ADJ cana-844 319 3 naive naive ADJ cana-844 319 4 bayes bayes NOUN cana-844 319 5 ( ( PUNCT cana-844 319 6 gbn gbn NOUN cana-844 319 7 ) ) PUNCT cana-844 319 8 model model NOUN cana-844 319 9 performs perform VERB cana-844 319 10 well well ADV cana-844 319 11 with with ADP cana-844 319 12 an an DET cana-844 319 13 f1 f1 ADJ cana-844 319 14 score score NOUN cana-844 319 15 of of ADP cana-844 319 16 94.54889 94.54889 NUM cana-844 319 17 % % NOUN cana-844 319 18 , , PUNCT cana-844 319 19 proving prove VERB cana-844 319 20 its its PRON cana-844 319 21 communications communication NOUN cana-844 319 22 on on ADP cana-844 319 23 applied apply VERB cana-844 319 24 nonlinear nonlinear ADJ cana-844 319 25 analysis analysis NOUN cana-844 319 26 issn issn NOUN cana-844 319 27 : : PUNCT cana-844 319 28 1074 1074 NUM cana-844 319 29 - - PUNCT cana-844 319 30 133x 133x NUM cana-844 319 31 vol vol NOUN cana-844 319 32 31 31 NUM cana-844 319 33 no no NOUN cana-844 319 34 . . PUNCT cana-844 320 1 4s 4s NUM cana-844 320 2 ( ( PUNCT cana-844 320 3 2024 2024 NUM cana-844 320 4 ) ) PUNCT cana-844 320 5 250 250 NUM cana-844 320 6 https://internationalpubls.com https://internationalpubls.com X cana-844 320 7 effectiveness effectiveness NOUN cana-844 320 8 in in ADP cana-844 320 9 classification classification NOUN cana-844 320 10 tasks task NOUN cana-844 320 11 . . PUNCT cana-844 321 1 in in ADP cana-844 321 2 contrast contrast NOUN cana-844 321 3 , , PUNCT cana-844 321 4 logistic logistic ADJ cana-844 321 5 regression regression NOUN cana-844 321 6 ( ( PUNCT cana-844 321 7 lr lr NOUN cana-844 321 8 ) ) PUNCT cana-844 321 9 and and CCONJ cana-844 321 10 k k ADV cana-844 321 11 - - PUNCT cana-844 321 12 nearest near ADJ cana-844 321 13 neighbors neighbor NOUN cana-844 321 14 ( ( PUNCT cana-844 321 15 knn knn PROPN cana-844 321 16 ) ) PUNCT cana-844 321 17 show show VERB cana-844 321 18 slightly slightly ADV cana-844 321 19 lower low ADJ cana-844 321 20 f1 f1 NOUN cana-844 321 21 scores score NOUN cana-844 321 22 of of ADP cana-844 321 23 91.10771 91.10771 NUM cana-844 321 24 % % NOUN cana-844 321 25 and and CCONJ cana-844 321 26 93.94778 93.94778 NUM cana-844 321 27 % % NOUN cana-844 321 28 , , PUNCT cana-844 321 29 respectively respectively ADV cana-844 321 30 , , PUNCT cana-844 321 31 suggesting suggest VERB cana-844 321 32 a a DET cana-844 321 33 less less ADV cana-844 321 34 balanced balanced ADJ cana-844 321 35 precision precision NOUN cana-844 321 36 - - PUNCT cana-844 321 37 recall recall NOUN cana-844 321 38 trade trade NOUN cana-844 321 39 - - PUNCT cana-844 321 40 off off NOUN cana-844 321 41 . . PUNCT cana-844 322 1 these these DET cana-844 322 2 f1 f1 PROPN cana-844 322 3 scores score NOUN cana-844 322 4 reveal reveal VERB cana-844 322 5 insights insight NOUN cana-844 322 6 into into ADP cana-844 322 7 the the DET cana-844 322 8 strengths strength NOUN cana-844 322 9 and and CCONJ cana-844 322 10 weaknesses weakness NOUN cana-844 322 11 of of ADP cana-844 322 12 each each DET cana-844 322 13 model model NOUN cana-844 322 14 , , PUNCT cana-844 322 15 helping help VERB cana-844 322 16 with with ADP cana-844 322 17 potential potential ADJ cana-844 322 18 optimizations optimization NOUN cana-844 322 19 to to PART cana-844 322 20 improve improve VERB cana-844 322 21 overall overall ADJ cana-844 322 22 classification classification NOUN cana-844 322 23 performance performance NOUN cana-844 322 24 . . PUNCT cana-844 323 1 the the DET cana-844 323 2 time time NOUN cana-844 323 3 it it PRON cana-844 323 4 takes take VERB cana-844 323 5 to to PART cana-844 323 6 train train VERB cana-844 323 7 in in ADP cana-844 323 8 seconds second NOUN cana-844 323 9 is be AUX cana-844 323 10 a a DET cana-844 323 11 key key ADJ cana-844 323 12 measure measure NOUN cana-844 323 13 for for ADP cana-844 323 14 assessing assess VERB cana-844 323 15 how how SCONJ cana-844 323 16 efficient efficient ADJ cana-844 323 17 different different ADJ cana-844 323 18 models model NOUN cana-844 323 19 are be AUX cana-844 323 20 when when SCONJ cana-844 323 21 using use VERB cana-844 323 22 the the DET cana-844 323 23 resnet50 resnet50 NOUN cana-844 323 24 design design NOUN cana-844 323 25 for for ADP cana-844 323 26 image image NOUN cana-844 323 27 classification classification NOUN cana-844 323 28 jobs job NOUN cana-844 323 29 . . PUNCT cana-844 324 1 fig fig NOUN cana-844 324 2 17 17 NUM cana-844 324 3 displays display VERB cana-844 324 4 the the DET cana-844 324 5 graphical graphical ADJ cana-844 324 6 representation representation NOUN cana-844 324 7 training training NOUN cana-844 324 8 time time NOUN cana-844 324 9 in in ADP cana-844 324 10 seconds second NOUN cana-844 324 11 for for ADP cana-844 324 12 each each DET cana-844 324 13 model model NOUN cana-844 324 14 utilizing utilize VERB cana-844 324 15 resnet50 resnet50 NOUN cana-844 324 16 . . PUNCT cana-844 325 1 fig fig NOUN cana-844 325 2 17 17 NUM cana-844 325 3 : : PUNCT cana-844 325 4 graphical graphical ADJ cana-844 325 5 representation representation NOUN cana-844 325 6 of of ADP cana-844 325 7 the the DET cana-844 325 8 training training NOUN cana-844 325 9 time time NOUN cana-844 325 10 in in ADP cana-844 325 11 seconds second NOUN cana-844 325 12 for for ADP cana-844 325 13 each each DET cana-844 325 14 model model NOUN cana-844 325 15 utilizing utilize VERB cana-844 325 16 resnet50 resnet50 NOUN cana-844 325 17 notably notably ADV cana-844 325 18 , , PUNCT cana-844 325 19 the the DET cana-844 325 20 k k NOUN cana-844 325 21 - - PUNCT cana-844 325 22 nearest near ADJ cana-844 325 23 neighbors neighbor NOUN cana-844 325 24 ( ( PUNCT cana-844 325 25 knn knn PROPN cana-844 325 26 ) ) PUNCT cana-844 325 27 , , PUNCT cana-844 325 28 logistic logistic ADJ cana-844 325 29 regression regression NOUN cana-844 325 30 ( ( PUNCT cana-844 325 31 lr lr NOUN cana-844 325 32 ) ) PUNCT cana-844 325 33 , , PUNCT cana-844 325 34 and and CCONJ cana-844 325 35 gaussian gaussian ADJ cana-844 325 36 naive naive ADJ cana-844 325 37 bayes bayes NOUN cana-844 325 38 ( ( PUNCT cana-844 325 39 gbn gbn NOUN cana-844 325 40 ) ) PUNCT cana-844 325 41 models model NOUN cana-844 325 42 all all PRON cana-844 325 43 have have VERB cana-844 325 44 very very ADV cana-844 325 45 short short ADJ cana-844 325 46 training training NOUN cana-844 325 47 times time NOUN cana-844 325 48 of of ADP cana-844 325 49 just just ADV cana-844 325 50 1 1 NUM cana-844 325 51 second second ADJ cana-844 325 52 , , PUNCT cana-844 325 53 highlighting highlight VERB cana-844 325 54 their their PRON cana-844 325 55 computational computational ADJ cana-844 325 56 efficiency efficiency NOUN cana-844 325 57 in in ADP cana-844 325 58 training train VERB cana-844 325 59 the the DET cana-844 325 60 model model NOUN cana-844 325 61 . . PUNCT cana-844 326 1 even even ADV cana-844 326 2 though though SCONJ cana-844 326 3 the the DET cana-844 326 4 random random ADJ cana-844 326 5 forest forest NOUN cana-844 326 6 classifier classifier NOUN cana-844 326 7 ( ( PUNCT cana-844 326 8 rfc rfc PROPN cana-844 326 9 ) ) PUNCT cana-844 326 10 is be AUX cana-844 326 11 efficient efficient ADJ cana-844 326 12 , , PUNCT cana-844 326 13 it it PRON cana-844 326 14 takes take VERB cana-844 326 15 about about ADV cana-844 326 16 7 7 NUM cana-844 326 17 seconds second NOUN cana-844 326 18 longer long ADV cana-844 326 19 to to PART cana-844 326 20 train train VERB cana-844 326 21 , , PUNCT cana-844 326 22 possibly possibly ADV cana-844 326 23 because because SCONJ cana-844 326 24 of of ADP cana-844 326 25 its its PRON cana-844 326 26 ensemble ensemble ADJ cana-844 326 27 learning learning NOUN cana-844 326 28 approach approach NOUN cana-844 326 29 and and CCONJ cana-844 326 30 complexity complexity NOUN cana-844 326 31 . . PUNCT cana-844 327 1 the the DET cana-844 327 2 sequential sequential ADJ cana-844 327 3 model model NOUN cana-844 327 4 , , PUNCT cana-844 327 5 which which PRON cana-844 327 6 achieves achieve VERB cana-844 327 7 the the DET cana-844 327 8 best good ADJ cana-844 327 9 classification classification NOUN cana-844 327 10 performance performance NOUN cana-844 327 11 , , PUNCT cana-844 327 12 requires require VERB cana-844 327 13 a a DET cana-844 327 14 longer long ADV cana-844 327 15 training training NOUN cana-844 327 16 time time NOUN cana-844 327 17 of of ADP cana-844 327 18 11 11 NUM cana-844 327 19 seconds second NOUN cana-844 327 20 , , PUNCT cana-844 327 21 likely likely ADJ cana-844 327 22 due due ADP cana-844 327 23 to to ADP cana-844 327 24 its its PRON cana-844 327 25 deep deep ADJ cana-844 327 26 learning learning NOUN cana-844 327 27 architecture architecture NOUN cana-844 327 28 and and CCONJ cana-844 327 29 extensive extensive ADJ cana-844 327 30 parameter parameter NOUN cana-844 327 31 tuning tuning NOUN cana-844 327 32 . . PUNCT cana-844 328 1 these these DET cana-844 328 2 insights insight NOUN cana-844 328 3 on on ADP cana-844 328 4 training training NOUN cana-844 328 5 times time NOUN cana-844 328 6 are be AUX cana-844 328 7 important important ADJ cana-844 328 8 when when SCONJ cana-844 328 9 choosing choose VERB cana-844 328 10 a a DET cana-844 328 11 model model NOUN cana-844 328 12 , , PUNCT cana-844 328 13 especially especially ADV cana-844 328 14 in in ADP cana-844 328 15 situations situation NOUN cana-844 328 16 with with ADP cana-844 328 17 limited limited ADJ cana-844 328 18 computational computational ADJ cana-844 328 19 resources resource NOUN cana-844 328 20 or or CCONJ cana-844 328 21 time time NOUN cana-844 328 22 constraints constraint NOUN cana-844 328 23 , , PUNCT cana-844 328 24 helping help VERB cana-844 328 25 researchers researcher NOUN cana-844 328 26 pick pick VERB cana-844 328 27 the the DET cana-844 328 28 most most ADV cana-844 328 29 suitable suitable ADJ cana-844 328 30 model model NOUN cana-844 328 31 for for ADP cana-844 328 32 their their PRON cana-844 328 33 needs need NOUN cana-844 328 34 . . PUNCT cana-844 329 1 in in ADP cana-844 329 2 conclusion conclusion NOUN cana-844 329 3 , , PUNCT cana-844 329 4 the the DET cana-844 329 5 analysis analysis NOUN cana-844 329 6 of of ADP cana-844 329 7 the the DET cana-844 329 8 results result NOUN cana-844 329 9 reveals reveal VERB cana-844 329 10 important important ADJ cana-844 329 11 findings finding NOUN cana-844 329 12 about about ADP cana-844 329 13 how how SCONJ cana-844 329 14 well well ADV cana-844 329 15 various various ADJ cana-844 329 16 models model NOUN cana-844 329 17 perform perform VERB cana-844 329 18 and and CCONJ cana-844 329 19 how how SCONJ cana-844 329 20 efficient efficient ADJ cana-844 329 21 they they PRON cana-844 329 22 are be AUX cana-844 329 23 when when SCONJ cana-844 329 24 used use VERB cana-844 329 25 for for ADP cana-844 329 26 image image NOUN cana-844 329 27 classification classification NOUN cana-844 329 28 tasks task NOUN cana-844 329 29 with with ADP cana-844 329 30 vgg19 vgg19 PROPN cana-844 329 31 and and CCONJ cana-844 329 32 resnet50 resnet50 VERB cana-844 329 33 architecture architecture NOUN cana-844 329 34 . . PUNCT cana-844 330 1 6 6 X cana-844 330 2 . . X cana-844 330 3 conclusion conclusion NOUN cana-844 330 4 and and CCONJ cana-844 330 5 future future ADJ cana-844 330 6 scope scope NOUN cana-844 330 7 in in ADP cana-844 330 8 conclusion conclusion NOUN cana-844 330 9 , , PUNCT cana-844 330 10 combining combine VERB cana-844 330 11 radiological radiological ADJ cana-844 330 12 imaging imaging NOUN cana-844 330 13 with with ADP cana-844 330 14 genomic genomic ADJ cana-844 330 15 data datum NOUN cana-844 330 16 via via ADP cana-844 330 17 radiogenomics radiogenomic NOUN cana-844 330 18 shows show NOUN cana-844 330 19 promise promise VERB cana-844 330 20 in in ADP cana-844 330 21 enhancing enhance VERB cana-844 330 22 the the DET cana-844 330 23 diagnosis diagnosis NOUN cana-844 330 24 and and CCONJ cana-844 330 25 treatment treatment NOUN cana-844 330 26 of of ADP cana-844 330 27 aggressive aggressive ADJ cana-844 330 28 brain brain NOUN cana-844 330 29 tumors tumor NOUN cana-844 330 30 such such ADJ cana-844 330 31 as as ADP cana-844 330 32 glioblastomas glioblastoma NOUN cana-844 330 33 . . PUNCT cana-844 331 1 recent recent ADJ cana-844 331 2 communications communication NOUN cana-844 331 3 on on ADP cana-844 331 4 applied apply VERB cana-844 331 5 nonlinear nonlinear ADJ cana-844 331 6 analysis analysis NOUN cana-844 331 7 issn issn NOUN cana-844 331 8 : : PUNCT cana-844 331 9 1074 1074 NUM cana-844 331 10 - - PUNCT cana-844 331 11 133x 133x NUM cana-844 331 12 vol vol NOUN cana-844 331 13 31 31 NUM cana-844 331 14 no no NOUN cana-844 331 15 . . PUNCT cana-844 332 1 4s 4s NUM cana-844 332 2 ( ( PUNCT cana-844 332 3 2024 2024 NUM cana-844 332 4 ) ) PUNCT cana-844 332 5 251 251 NUM cana-844 332 6 https://internationalpubls.com https://internationalpubls.com X cana-844 332 7 research research NOUN cana-844 332 8 has have AUX cana-844 332 9 highlighted highlight VERB cana-844 332 10 the the DET cana-844 332 11 potential potential NOUN cana-844 332 12 of of ADP cana-844 332 13 using use VERB cana-844 332 14 deep deep ADJ cana-844 332 15 learning learning NOUN cana-844 332 16 and and CCONJ cana-844 332 17 machine machine NOUN cana-844 332 18 learning learning NOUN cana-844 332 19 methods method NOUN cana-844 332 20 to to PART cana-844 332 21 noninvasively noninvasively ADV cana-844 332 22 predict predict VERB cana-844 332 23 mgmt mgmt PROPN cana-844 332 24 promoter promoter NOUN cana-844 332 25 methylation methylation NOUN cana-844 332 26 status status NOUN cana-844 332 27 , , PUNCT cana-844 332 28 addressing address VERB cana-844 332 29 a a DET cana-844 332 30 significant significant ADJ cana-844 332 31 challenge challenge NOUN cana-844 332 32 in in ADP cana-844 332 33 managing manage VERB cana-844 332 34 glioblastomas glioblastoma NOUN cana-844 332 35 . . PUNCT cana-844 333 1 by by ADP cana-844 333 2 utilizing utilize VERB cana-844 333 3 advanced advanced ADJ cana-844 333 4 techniques technique NOUN cana-844 333 5 like like ADP cana-844 333 6 vgg19 vgg19 INTJ cana-844 333 7 and and CCONJ cana-844 333 8 resnet50 resnet50 VERB cana-844 333 9 for for ADP cana-844 333 10 feature feature NOUN cana-844 333 11 extraction extraction NOUN cana-844 333 12 , , PUNCT cana-844 333 13 random random ADJ cana-844 333 14 forest forest NOUN cana-844 333 15 for for ADP cana-844 333 16 feature feature NOUN cana-844 333 17 selection selection NOUN cana-844 333 18 , , PUNCT cana-844 333 19 and and CCONJ cana-844 333 20 various various ADJ cana-844 333 21 classification classification NOUN cana-844 333 22 algorithms algorithm NOUN cana-844 333 23 for for ADP cana-844 333 24 prediction prediction NOUN cana-844 333 25 , , PUNCT cana-844 333 26 this this DET cana-844 333 27 study study NOUN cana-844 333 28 has have AUX cana-844 333 29 successfully successfully ADV cana-844 333 30 provided provide VERB cana-844 333 31 accurate accurate ADJ cana-844 333 32 estimations estimation NOUN cana-844 333 33 of of ADP cana-844 333 34 mgmt mgmt PROPN cana-844 333 35 promoter promoter NOUN cana-844 333 36 methylation methylation NOUN cana-844 333 37 status status NOUN cana-844 333 38 . . PUNCT cana-844 334 1 the the DET cana-844 334 2 results result NOUN cana-844 334 3 emphasize emphasize VERB cana-844 334 4 that that SCONJ cana-844 334 5 using use VERB cana-844 334 6 sequential sequential ADJ cana-844 334 7 fcnet fcnet NOUN cana-844 334 8 ann ann PROPN cana-844 334 9 with with ADP cana-844 334 10 resnet50 resnet50 NOUN cana-844 334 11 is be AUX cana-844 334 12 the the DET cana-844 334 13 most most ADV cana-844 334 14 effective effective ADJ cana-844 334 15 algorithm algorithm NOUN cana-844 334 16 in in ADP cana-844 334 17 this this DET cana-844 334 18 situation situation NOUN cana-844 334 19 . . PUNCT cana-844 335 1 additionally additionally ADV cana-844 335 2 , , PUNCT cana-844 335 3 the the DET cana-844 335 4 model model NOUN cana-844 335 5 's 's PART cana-844 335 6 robustness robustness NOUN cana-844 335 7 is be AUX cana-844 335 8 enhanced enhance VERB cana-844 335 9 by by ADP cana-844 335 10 thorough thorough ADJ cana-844 335 11 preprocessing preprocessing NOUN cana-844 335 12 steps step NOUN cana-844 335 13 such such ADJ cana-844 335 14 as as ADP cana-844 335 15 resizing resizing NOUN cana-844 335 16 images image NOUN cana-844 335 17 , , PUNCT cana-844 335 18 normalizing normalize VERB cana-844 335 19 features feature NOUN cana-844 335 20 , , PUNCT cana-844 335 21 and and CCONJ cana-844 335 22 handling handle VERB cana-844 335 23 class class NOUN cana-844 335 24 imbalances imbalance NOUN cana-844 335 25 . . PUNCT cana-844 336 1 blending blend VERB cana-844 336 2 radiological radiological ADJ cana-844 336 3 and and CCONJ cana-844 336 4 genomic genomic ADJ cana-844 336 5 characteristics characteristic NOUN cana-844 336 6 in in ADP cana-844 336 7 a a DET cana-844 336 8 cohesive cohesive ADJ cana-844 336 9 framework framework NOUN cana-844 336 10 is be AUX cana-844 336 11 a a DET cana-844 336 12 crucial crucial ADJ cana-844 336 13 advancement advancement NOUN cana-844 336 14 for for ADP cana-844 336 15 precision precision NOUN cana-844 336 16 healthcare healthcare NOUN cana-844 336 17 in in ADP cana-844 336 18 neuro neuro NOUN cana-844 336 19 - - PUNCT cana-844 336 20 oncology oncology NOUN cana-844 336 21 . . PUNCT cana-844 337 1 this this DET cana-844 337 2 progress progress NOUN cana-844 337 3 enables enable VERB cana-844 337 4 customized customized ADJ cana-844 337 5 and and CCONJ cana-844 337 6 efficient efficient ADJ cana-844 337 7 treatments treatment NOUN cana-844 337 8 for for ADP cana-844 337 9 individuals individual NOUN cana-844 337 10 with with ADP cana-844 337 11 glioblastomas glioblastoma NOUN cana-844 337 12 and and CCONJ cana-844 337 13 other other ADJ cana-844 337 14 aggressive aggressive ADJ cana-844 337 15 brain brain NOUN cana-844 337 16 tumors tumor NOUN cana-844 337 17 . . PUNCT cana-844 338 1 in in ADP cana-844 338 2 the the DET cana-844 338 3 future future NOUN cana-844 338 4 , , PUNCT cana-844 338 5 this this DET cana-844 338 6 research research NOUN cana-844 338 7 aims aim VERB cana-844 338 8 to to PART cana-844 338 9 improve improve VERB cana-844 338 10 and and CCONJ cana-844 338 11 confirm confirm VERB cana-844 338 12 the the DET cana-844 338 13 created create VERB cana-844 338 14 model model NOUN cana-844 338 15 using use VERB cana-844 338 16 bigger big ADJ cana-844 338 17 and and CCONJ cana-844 338 18 more more ADV cana-844 338 19 varied varied ADJ cana-844 338 20 datasets dataset NOUN cana-844 338 21 to to PART cana-844 338 22 make make VERB cana-844 338 23 it it PRON cana-844 338 24 more more ADV cana-844 338 25 widely widely ADV cana-844 338 26 applicable applicable ADJ cana-844 338 27 in in ADP cana-844 338 28 clinical clinical ADJ cana-844 338 29 settings setting NOUN cana-844 338 30 . . PUNCT cana-844 339 1 references reference NOUN cana-844 339 2 [ [ X cana-844 339 3 1 1 NUM cana-844 339 4 ] ] PUNCT cana-844 339 5 n. n. PROPN cana-844 339 6 q. q. PROPN cana-844 339 7 k. k. PROPN cana-844 339 8 le le PROPN cana-844 339 9 , , PUNCT cana-844 339 10 d. d. PROPN cana-844 339 11 thi thi PROPN cana-844 339 12 , , PUNCT cana-844 339 13 f. f. PROPN cana-844 339 14 y. y. PROPN cana-844 339 15 chiu chiu PROPN cana-844 339 16 , , PUNCT cana-844 339 17 e. e. PROPN cana-844 339 18 k. k. PROPN cana-844 340 1 y. y. PROPN cana-844 340 2 yapp yapp PROPN cana-844 340 3 , , PUNCT cana-844 340 4 h. h. PROPN cana-844 340 5 yeh yeh PROPN cana-844 340 6 , , PUNCT cana-844 340 7 and and CCONJ cana-844 340 8 c.-y c.-y NOUN cana-844 340 9 . . PUNCT cana-844 341 1 chen chen PROPN cana-844 341 2 , , PUNCT cana-844 341 3 β€œ " PUNCT cana-844 341 4 xgboost xgboost X cana-844 341 5 improves improve VERB cana-844 341 6 classification classification NOUN cana-844 341 7 of of ADP cana-844 341 8 mgmt mgmt PROPN cana-844 341 9 promoter promoter NOUN cana-844 341 10 methylation methylation NOUN cana-844 341 11 status status NOUN cana-844 341 12 in in ADP cana-844 341 13 idh1 idh1 PROPN cana-844 341 14 wildtype wildtype NOUN cana-844 341 15 glioblastoma glioblastoma NOUN cana-844 341 16 , , PUNCT cana-844 341 17 ” " PUNCT cana-844 341 18 journal journal NOUN cana-844 341 19 of of ADP cana-844 341 20 personalized personalized ADJ cana-844 341 21 medicine medicine NOUN cana-844 341 22 , , PUNCT cana-844 341 23 vol vol NOUN cana-844 341 24 . . PROPN cana-844 342 1 10 10 NUM cana-844 342 2 , , PUNCT cana-844 342 3 no no INTJ cana-844 342 4 . . NOUN cana-844 342 5 3 3 NUM cana-844 342 6 , , PUNCT cana-844 342 7 p. p. NOUN cana-844 342 8 128 128 NUM cana-844 342 9 , , PUNCT cana-844 342 10 sep sep PROPN cana-844 342 11 . . PROPN cana-844 343 1 2020 2020 NUM cana-844 343 2 , , PUNCT cana-844 343 3 doi doi NOUN cana-844 343 4 : : PUNCT cana-844 343 5 10.3390 10.3390 NUM cana-844 343 6 / / SYM cana-844 343 7 jpm10030128 jpm10030128 NOUN cana-844 343 8 . . PUNCT cana-844 344 1 [ [ X cana-844 344 2 2 2 NUM cana-844 344 3 ] ] PUNCT cana-844 344 4 x. x. NOUN cana-844 344 5 chen chen PROPN cana-844 344 6 et et PROPN cana-844 344 7 al al PROPN cana-844 344 8 . . PROPN cana-844 344 9 , , PUNCT cana-844 344 10 β€œ " PUNCT cana-844 344 11 automatic automatic ADJ cana-844 344 12 prediction prediction NOUN cana-844 344 13 of of ADP cana-844 344 14 mgmt mgmt PROPN cana-844 344 15 status status NOUN cana-844 344 16 in in ADP cana-844 344 17 glioblastoma glioblastoma NOUN cana-844 344 18 via via ADP cana-844 344 19 deep deep ADJ cana-844 344 20 learning learning NOUN cana-844 344 21 - - PUNCT cana-844 344 22 based base VERB cana-844 344 23 mr mr PROPN cana-844 344 24 image image NOUN cana-844 344 25 analysis analysis NOUN cana-844 344 26 , , PUNCT cana-844 344 27 ” " PUNCT cana-844 344 28 biomed biome VERB cana-844 344 29 research research NOUN cana-844 344 30 international international ADJ cana-844 344 31 , , PUNCT cana-844 344 32 vol vol NOUN cana-844 344 33 . . PUNCT cana-844 345 1 2020 2020 NUM cana-844 345 2 , , PUNCT cana-844 345 3 pp pp ADV cana-844 345 4 . . PUNCT cana-844 346 1 1–9 1–9 NUM cana-844 346 2 , , PUNCT cana-844 346 3 sep sep PROPN cana-844 346 4 . . PROPN cana-844 347 1 2020 2020 NUM cana-844 347 2 , , PUNCT cana-844 347 3 doi doi NOUN cana-844 347 4 : : PUNCT cana-844 347 5 10.1155/2020/9258649 10.1155/2020/9258649 NUM cana-844 347 6 . . PUNCT cana-844 348 1 [ [ X cana-844 348 2 3 3 NUM cana-844 348 3 ] ] X cana-844 348 4 c. c. PROPN cana-844 348 5 g. g. PROPN cana-844 348 6 b. b. PROPN cana-844 348 7 yogananda yogananda PROPN cana-844 348 8 et et PROPN cana-844 348 9 al al PROPN cana-844 348 10 . . PROPN cana-844 348 11 , , PUNCT cana-844 348 12 β€œ " PUNCT cana-844 348 13 mri mri NOUN cana-844 348 14 - - PUNCT cana-844 348 15 based base VERB cana-844 348 16 deep deep ADJ cana-844 348 17 - - PUNCT cana-844 348 18 learning learn VERB cana-844 348 19 method method NOUN cana-844 348 20 for for ADP cana-844 348 21 determining determine VERB cana-844 348 22 glioma glioma ADJ cana-844 348 23 mgmt mgmt NOUN cana-844 348 24 promoter promoter NOUN cana-844 348 25 methylation methylation NOUN cana-844 348 26 status status NOUN cana-844 348 27 , , PUNCT cana-844 348 28 ” " PUNCT cana-844 348 29 american american ADJ cana-844 348 30 journal journal PROPN cana-844 348 31 of of ADP cana-844 348 32 neuroradiology neuroradiology NOUN cana-844 348 33 , , PUNCT cana-844 348 34 vol vol NOUN cana-844 348 35 . . PROPN cana-844 349 1 42 42 NUM cana-844 349 2 , , PUNCT cana-844 349 3 no no INTJ cana-844 349 4 . . NOUN cana-844 349 5 5 5 NUM cana-844 349 6 , , PUNCT cana-844 349 7 pp pp ADJ cana-844 349 8 . . PUNCT cana-844 350 1 845–852 845–852 NUM cana-844 350 2 , , PUNCT cana-844 350 3 mar mar PROPN cana-844 350 4 . . PROPN cana-844 350 5 2021 2021 NUM cana-844 350 6 , , PUNCT cana-844 350 7 doi doi NOUN cana-844 350 8 : : PUNCT cana-844 350 9 10.3174 10.3174 NUM cana-844 350 10 / / SYM cana-844 350 11 ajnr.a7029 ajnr.a7029 NOUN cana-844 350 12 . . PUNCT cana-844 351 1 [ [ X cana-844 351 2 4 4 X cana-844 351 3 ] ] X cana-844 351 4 m. m. NOUN cana-844 351 5 v. v. ADP cana-844 351 6 a. a. PROPN cana-844 351 7 rao rao PROPN cana-844 351 8 , , PUNCT cana-844 351 9 β€œ " PUNCT cana-844 351 10 novel novel ADJ cana-844 351 11 local local ADJ cana-844 351 12 radiomic radiomic ADJ cana-844 351 13 bayesian bayesian NOUN cana-844 351 14 classifiers classifier NOUN cana-844 351 15 for for ADP cana-844 351 16 non non ADJ cana-844 351 17 - - ADJ cana-844 351 18 invasive invasive ADJ cana-844 351 19 prediction prediction NOUN cana-844 351 20 of of ADP cana-844 351 21 mgmt mgmt PROPN cana-844 351 22 methylation methylation PROPN cana-844 351 23 status status NOUN cana-844 351 24 in in ADP cana-844 351 25 glioblastoma glioblastoma NOUN cana-844 351 26 , , PUNCT cana-844 351 27 ” " PUNCT cana-844 351 28 arxiv arxiv PROPN cana-844 351 29 ( ( PUNCT cana-844 351 30 cornell cornell PROPN cana-844 351 31 university university PROPN cana-844 351 32 ) ) PUNCT cana-844 351 33 , , PUNCT cana-844 351 34 nov nov PROPN cana-844 351 35 . . PROPN cana-844 351 36 2021 2021 NUM cana-844 351 37 , , PUNCT cana-844 352 1 [ [ X cana-844 352 2 online online X cana-844 352 3 ] ] X cana-844 352 4 . . PUNCT cana-844 353 1 available available ADJ cana-844 353 2 : : PUNCT cana-844 354 1 http://arxiv.org/abs/2112.03259 http://arxiv.org/abs/2112.03259 X cana-844 354 2 . . PUNCT cana-844 355 1 [ [ X cana-844 355 2 5 5 X cana-844 355 3 ] ] PUNCT cana-844 355 4 e. e. PROPN cana-844 355 5 calabrese calabrese PROPN cana-844 355 6 et et PROPN cana-844 355 7 al al PROPN cana-844 355 8 . . PROPN cana-844 355 9 , , PUNCT cana-844 355 10 β€œ " PUNCT cana-844 355 11 combining combine VERB cana-844 355 12 radiomics radiomic NOUN cana-844 355 13 and and CCONJ cana-844 355 14 deep deep ADJ cana-844 355 15 convolutional convolutional ADJ cana-844 355 16 neural neural ADJ cana-844 355 17 network network NOUN cana-844 355 18 features feature VERB cana-844 355 19 from from ADP cana-844 355 20 preoperative preoperative ADJ cana-844 355 21 mri mri NOUN cana-844 355 22 for for ADP cana-844 355 23 predicting predict VERB cana-844 355 24 clinically clinically ADV cana-844 355 25 relevant relevant ADJ cana-844 355 26 genetic genetic ADJ cana-844 355 27 biomarkers biomarker NOUN cana-844 355 28 in in ADP cana-844 355 29 glioblastoma glioblastoma NOUN cana-844 355 30 , , PUNCT cana-844 355 31 ” " PUNCT cana-844 355 32 neuro neuro ADJ cana-844 355 33 - - PUNCT cana-844 355 34 oncology oncology NOUN cana-844 355 35 advances advance NOUN cana-844 355 36 , , PUNCT cana-844 355 37 vol vol NOUN cana-844 355 38 . . PROPN cana-844 355 39 4 4 NUM cana-844 355 40 , , PUNCT cana-844 355 41 no no INTJ cana-844 355 42 . . NOUN cana-844 355 43 1 1 NUM cana-844 355 44 , , PUNCT cana-844 355 45 jan jan PROPN cana-844 355 46 . . PROPN cana-844 355 47 2022 2022 NUM cana-844 355 48 , , PUNCT cana-844 355 49 doi doi NOUN cana-844 355 50 : : PUNCT cana-844 355 51 10.1093 10.1093 NUM cana-844 355 52 / / SYM cana-844 355 53 noajnl noajnl PROPN cana-844 355 54 / / SYM cana-844 355 55 vdac060 vdac060 PROPN cana-844 355 56 . . PUNCT cana-844 356 1 [ [ X cana-844 356 2 6 6 NUM cana-844 356 3 ] ] PUNCT cana-844 356 4 s. s. PROPN cana-844 356 5 chen chen PROPN cana-844 356 6 et et PROPN cana-844 356 7 al al PROPN cana-844 356 8 . . PROPN cana-844 356 9 , , PUNCT cana-844 356 10 β€œ " PUNCT cana-844 356 11 predicting predict VERB cana-844 356 12 mgmt mgmt PROPN cana-844 356 13 promoter promoter NOUN cana-844 356 14 methylation methylation NOUN cana-844 356 15 in in ADP cana-844 356 16 diffuse diffuse ADJ cana-844 356 17 gliomas glioma NOUN cana-844 356 18 using use VERB cana-844 356 19 deep deep ADJ cana-844 356 20 learning learning NOUN cana-844 356 21 with with ADP cana-844 356 22 radiomics radiomic NOUN cana-844 356 23 , , PUNCT cana-844 356 24 ” " PUNCT cana-844 356 25 journal journal NOUN cana-844 356 26 of of ADP cana-844 356 27 clinical clinical ADJ cana-844 356 28 medicine medicine NOUN cana-844 356 29 , , PUNCT cana-844 356 30 vol vol NOUN cana-844 356 31 . . PROPN cana-844 356 32 11 11 NUM cana-844 356 33 , , PUNCT cana-844 356 34 no no INTJ cana-844 356 35 . . NOUN cana-844 356 36 12 12 NUM cana-844 356 37 , , PUNCT cana-844 356 38 p. p. NOUN cana-844 356 39 3445 3445 NUM cana-844 356 40 , , PUNCT cana-844 356 41 jun jun PROPN cana-844 356 42 . . PROPN cana-844 356 43 2022 2022 NUM cana-844 356 44 , , PUNCT cana-844 356 45 doi doi NOUN cana-844 356 46 : : PUNCT cana-844 356 47 10.3390 10.3390 NUM cana-844 356 48 / / SYM cana-844 356 49 jcm11123445 jcm11123445 NOUN cana-844 356 50 . . PUNCT cana-844 357 1 [ [ X cana-844 357 2 7 7 X cana-844 357 3 ] ] X cana-844 357 4 b. b. PROPN cana-844 357 5 kim kim PROPN cana-844 357 6 et et PROPN cana-844 357 7 al al PROPN cana-844 357 8 . . PROPN cana-844 357 9 , , PUNCT cana-844 357 10 β€œ " PUNCT cana-844 357 11 validation validation NOUN cana-844 357 12 of of ADP cana-844 357 13 mri mri NOUN cana-844 357 14 - - PUNCT cana-844 357 15 based base VERB cana-844 357 16 models model NOUN cana-844 357 17 to to PART cana-844 357 18 predict predict VERB cana-844 357 19 mgmt mgmt PROPN cana-844 357 20 promoter promoter NOUN cana-844 357 21 methylation methylation NOUN cana-844 357 22 in in ADP cana-844 357 23 gliomas glioma NOUN cana-844 357 24 : : PUNCT cana-844 357 25 brats brat NOUN cana-844 357 26 2021 2021 NUM cana-844 357 27 radiogenomics radiogenomic NOUN cana-844 357 28 challenge challenge NOUN cana-844 357 29 , , PUNCT cana-844 357 30 ” " PUNCT cana-844 357 31 cancers cancer NOUN cana-844 357 32 , , PUNCT cana-844 357 33 vol vol NOUN cana-844 357 34 . . PROPN cana-844 358 1 14 14 NUM cana-844 358 2 , , PUNCT cana-844 358 3 no no INTJ cana-844 358 4 . . NOUN cana-844 358 5 19 19 NUM cana-844 358 6 , , PUNCT cana-844 358 7 p. p. NOUN cana-844 358 8 4827 4827 NUM cana-844 358 9 , , PUNCT cana-844 358 10 oct oct PROPN cana-844 358 11 . . PROPN cana-844 358 12 2022 2022 NUM cana-844 358 13 , , PUNCT cana-844 358 14 doi doi NOUN cana-844 358 15 : : PUNCT cana-844 358 16 10.3390 10.3390 NUM cana-844 358 17 / / SYM cana-844 358 18 cancers14194827 cancers14194827 PROPN cana-844 358 19 . . PUNCT cana-844 359 1 [ [ X cana-844 359 2 8 8 NUM cana-844 359 3 ] ] PUNCT cana-844 359 4 a. a. NOUN cana-844 359 5 iranmehr iranmehr PROPN cana-844 359 6 , , PUNCT cana-844 359 7 s. s. PROPN cana-844 359 8 gutta gutta PROPN cana-844 359 9 , , PUNCT cana-844 359 10 and and CCONJ cana-844 359 11 a. a. NOUN cana-844 359 12 hadaegh hadaegh VERB cana-844 359 13 , , PUNCT cana-844 359 14 β€œ " PUNCT cana-844 359 15 improved improved ADJ cana-844 359 16 prediction prediction NOUN cana-844 359 17 of of ADP cana-844 359 18 mgmt mgmt PROPN cana-844 359 19 methylation methylation PROPN cana-844 359 20 status status NOUN cana-844 359 21 in in ADP cana-844 359 22 glioblastoma glioblastoma NOUN cana-844 359 23 using use VERB cana-844 359 24 a a DET cana-844 359 25 deep deep ADJ cana-844 359 26 attention attention NOUN cana-844 359 27 network network NOUN cana-844 359 28 , , PUNCT cana-844 359 29 ” " PUNCT cana-844 359 30 2022 2022 NUM cana-844 359 31 international international ADJ cana-844 359 32 conference conference NOUN cana-844 359 33 on on ADP cana-844 359 34 electrical electrical ADJ cana-844 359 35 , , PUNCT cana-844 359 36 computer computer NOUN cana-844 359 37 , , PUNCT cana-844 359 38 communications communication NOUN cana-844 359 39 and and CCONJ cana-844 359 40 mechatronics mechatronic NOUN cana-844 359 41 engineering engineering NOUN cana-844 359 42 ( ( PUNCT cana-844 359 43 iceccme iceccme NOUN cana-844 359 44 ) ) PUNCT cana-844 359 45 , , PUNCT cana-844 359 46 nov nov PROPN cana-844 359 47 . . PROPN cana-844 359 48 2022 2022 NUM cana-844 359 49 , , PUNCT cana-844 359 50 doi doi NOUN cana-844 359 51 : : PUNCT cana-844 359 52 10.1109 10.1109 NUM cana-844 359 53 / / SYM cana-844 359 54 iceccme55909.2022.9988694 iceccme55909.2022.9988694 PROPN cana-844 359 55 . . PUNCT cana-844 360 1 [ [ X cana-844 360 2 9 9 NUM cana-844 360 3 ] ] PUNCT cana-844 360 4 k. k. PROPN cana-844 360 5 r. r. PROPN cana-844 360 6 spoorthy spoorthy PROPN cana-844 360 7 , , PUNCT cana-844 360 8 a. a. PROPN cana-844 360 9 r. r. PROPN cana-844 360 10 mahdev mahdev PROPN cana-844 360 11 , , PUNCT cana-844 360 12 b. b. PROPN cana-844 360 13 vaishnav vaishnav PROPN cana-844 360 14 , , PUNCT cana-844 360 15 and and CCONJ cana-844 360 16 s. s. PROPN cana-844 360 17 m. m. PROPN cana-844 360 18 l. l. PROPN cana-844 360 19 j j PROPN cana-844 360 20 , , PUNCT cana-844 360 21 β€œ " PUNCT cana-844 360 22 deep deep ADJ cana-844 360 23 learning learning NOUN cana-844 360 24 approach approach NOUN cana-844 360 25 for for ADP cana-844 360 26 radiogenomic radiogenomic ADJ cana-844 360 27 classification classification NOUN cana-844 360 28 of of ADP cana-844 360 29 brain brain NOUN cana-844 360 30 tumor tumor NOUN cana-844 360 31 , , PUNCT cana-844 360 32 ” " PUNCT cana-844 360 33 2022 2022 NUM cana-844 360 34 ieee ieee NOUN cana-844 360 35 19th 19th ADJ cana-844 360 36 india india PROPN cana-844 360 37 council council PROPN cana-844 360 38 international international PROPN cana-844 360 39 conference conference PROPN cana-844 360 40 ( ( PUNCT cana-844 360 41 indicon indicon NOUN cana-844 360 42 ) ) PUNCT cana-844 360 43 , , PUNCT cana-844 360 44 nov nov PROPN cana-844 360 45 . . PROPN cana-844 360 46 2022 2022 NUM cana-844 360 47 , , PUNCT cana-844 360 48 doi doi NOUN cana-844 360 49 : : PUNCT cana-844 360 50 10.1109 10.1109 NUM cana-844 360 51 / / SYM cana-844 360 52 indicon56171.2022.10039760 indicon56171.2022.10039760 NOUN cana-844 360 53 . . PUNCT cana-844 361 1 [ [ X cana-844 361 2 10 10 NUM cana-844 361 3 ] ] X cana-844 361 4 l. l. PROPN cana-844 361 5 gatto gatto PROPN cana-844 361 6 et et PROPN cana-844 361 7 al al PROPN cana-844 361 8 . . PROPN cana-844 361 9 , , PUNCT cana-844 361 10 β€œ " PUNCT cana-844 361 11 beyond beyond ADP cana-844 361 12 imaging imaging NOUN cana-844 361 13 and and CCONJ cana-844 361 14 genetic genetic ADJ cana-844 361 15 signature signature NOUN cana-844 361 16 in in ADP cana-844 361 17 glioblastoma glioblastoma NOUN cana-844 361 18 : : PUNCT cana-844 361 19 radiogenomic radiogenomic ADJ cana-844 361 20 holistic holistic ADJ cana-844 361 21 approach approach NOUN cana-844 361 22 in in ADP cana-844 361 23 neuro neuro NOUN cana-844 361 24 - - PUNCT cana-844 361 25 oncology oncology NOUN cana-844 361 26 , , PUNCT cana-844 361 27 ” " PUNCT cana-844 361 28 biomedicines biomedicine NOUN cana-844 361 29 , , PUNCT cana-844 361 30 vol vol NOUN cana-844 361 31 . . PROPN cana-844 361 32 10 10 NUM cana-844 361 33 , , PUNCT cana-844 361 34 no no INTJ cana-844 361 35 . . NOUN cana-844 361 36 12 12 NUM cana-844 361 37 , , PUNCT cana-844 361 38 p. p. NOUN cana-844 361 39 3205 3205 NUM cana-844 361 40 , , PUNCT cana-844 361 41 dec dec PROPN cana-844 361 42 . . PROPN cana-844 361 43 2022 2022 NUM cana-844 361 44 , , PUNCT cana-844 361 45 doi doi NOUN cana-844 361 46 : : PUNCT cana-844 361 47 10.3390 10.3390 NUM cana-844 361 48 / / SYM cana-844 361 49 biomedicines10123205 biomedicines10123205 PROPN cana-844 361 50 . . PUNCT cana-844 362 1 [ [ X cana-844 362 2 11 11 NUM cana-844 362 3 ] ] PUNCT cana-844 362 4 s. s. PROPN cana-844 362 5 faghani faghani PROPN cana-844 362 6 , , PUNCT cana-844 362 7 b. b. PROPN cana-844 362 8 khosravi khosravi PROPN cana-844 362 9 , , PUNCT cana-844 362 10 m. m. NOUN cana-844 362 11 moassefi moassefi PROPN cana-844 362 12 , , PUNCT cana-844 362 13 g. g. PROPN cana-844 362 14 m. m. PROPN cana-844 362 15 conte conte PROPN cana-844 362 16 , , PUNCT cana-844 362 17 and and CCONJ cana-844 362 18 b. b. PROPN cana-844 362 19 j. j. PROPN cana-844 362 20 erickson erickson PROPN cana-844 362 21 , , PUNCT cana-844 362 22 β€œ " PUNCT cana-844 362 23 a a DET cana-844 362 24 comparison comparison NOUN cana-844 362 25 of of ADP cana-844 362 26 three three NUM cana-844 362 27 different different ADJ cana-844 362 28 deep deep ADJ cana-844 362 29 learning learning NOUN cana-844 362 30 - - PUNCT cana-844 362 31 based base VERB cana-844 362 32 models model NOUN cana-844 362 33 to to PART cana-844 362 34 predict predict VERB cana-844 362 35 the the DET cana-844 362 36 mgmt mgmt PROPN cana-844 362 37 promoter promoter NOUN cana-844 362 38 methylation methylation NOUN cana-844 362 39 status status NOUN cana-844 362 40 in in ADP cana-844 362 41 glioblastoma glioblastoma NOUN cana-844 362 42 using use VERB cana-844 362 43 brain brain NOUN cana-844 362 44 mri mri NOUN cana-844 362 45 , , PUNCT cana-844 362 46 ” " PUNCT cana-844 362 47 journal journal NOUN cana-844 362 48 of of ADP cana-844 362 49 digital digital ADJ cana-844 362 50 imaging imaging NOUN cana-844 362 51 , , PUNCT cana-844 362 52 vol vol NOUN cana-844 362 53 . . PROPN cana-844 362 54 36 36 NUM cana-844 362 55 , , PUNCT cana-844 362 56 no no INTJ cana-844 362 57 . . NOUN cana-844 362 58 3 3 NUM cana-844 362 59 , , PUNCT cana-844 362 60 pp pp ADJ cana-844 362 61 . . PUNCT cana-844 363 1 837–846 837–846 NUM cana-844 363 2 , , PUNCT cana-844 363 3 jan jan PROPN cana-844 363 4 . . PROPN cana-844 363 5 2023 2023 NUM cana-844 363 6 , , PUNCT cana-844 363 7 doi doi NOUN cana-844 363 8 : : PUNCT cana-844 363 9 10.1007 10.1007 NUM cana-844 363 10 / / SYM cana-844 363 11 s10278 s10278 NOUN cana-844 363 12 - - PUNCT cana-844 363 13 022 022 NUM cana-844 363 14 - - PUNCT cana-844 363 15 00757 00757 NUM cana-844 363 16 - - PUNCT cana-844 363 17 x. x. NOUN cana-844 364 1 [ [ X cana-844 364 2 12 12 NUM cana-844 364 3 ] ] PUNCT cana-844 364 4 sakly sakly NOUN cana-844 364 5 h h NOUN cana-844 364 6 , , PUNCT cana-844 364 7 said say VERB cana-844 364 8 m m ADV cana-844 364 9 , , PUNCT cana-844 364 10 seekins seekin VERB cana-844 364 11 j j PROPN cana-844 364 12 , , PUNCT cana-844 364 13 guetari guetari PROPN cana-844 364 14 r r PROPN cana-844 364 15 , , PUNCT cana-844 364 16 kraiem kraiem NOUN cana-844 364 17 n n CCONJ cana-844 364 18 , , PUNCT cana-844 364 19 marzougui marzougui PROPN cana-844 364 20 m. m. NOUN cana-844 364 21 brain brain PROPN cana-844 364 22 tumor tumor PROPN cana-844 364 23 radiogenomic radiogenomic ADJ cana-844 364 24 classification classification NOUN cana-844 364 25 of of ADP cana-844 364 26 o6 o6 PROPN cana-844 364 27 - - PUNCT cana-844 364 28 methylguanine methylguanine NOUN cana-844 364 29 - - PUNCT cana-844 364 30 dna dna NOUN cana-844 364 31 methyltransferase methyltransferase NOUN cana-844 364 32 promoter promoter NOUN cana-844 364 33 methylation methylation NOUN cana-844 364 34 in in ADP cana-844 364 35 malignant malignant ADJ cana-844 364 36 gliomas glioma NOUN cana-844 364 37 - - PUNCT cana-844 364 38 based base VERB cana-844 364 39 transfer transfer NOUN cana-844 364 40 learning learning NOUN cana-844 364 41 . . PUNCT cana-844 365 1 cancer cancer NOUN cana-844 365 2 control control NOUN cana-844 365 3 . . PUNCT cana-844 366 1 2023 2023 NUM cana-844 366 2 jan jan PROPN cana-844 366 3 - - PUNCT cana-844 366 4 dec;30:10732748231169149 dec;30:10732748231169149 NOUN cana-844 366 5 . . PUNCT cana-844 367 1 doi doi NOUN cana-844 367 2 : : PUNCT cana-844 367 3 10.1177/10732748231169149 10.1177/10732748231169149 NUM cana-844 367 4 . . PUNCT cana-844 368 1 pmid pmid NOUN cana-844 368 2 : : PUNCT cana-844 368 3 37078100 37078100 NUM cana-844 368 4 ; ; PUNCT cana-844 368 5 pmcid pmcid NOUN cana-844 368 6 : : PUNCT cana-844 368 7 pmc10126792 pmc10126792 ADJ cana-844 368 8 . . PUNCT cana-844 369 1 communications communication NOUN cana-844 369 2 on on ADP cana-844 369 3 applied apply VERB cana-844 369 4 nonlinear nonlinear ADJ cana-844 369 5 analysis analysis NOUN cana-844 369 6 issn issn NOUN cana-844 369 7 : : PUNCT cana-844 369 8 1074 1074 NUM cana-844 369 9 - - PUNCT cana-844 369 10 133x 133x NUM cana-844 369 11 vol vol NOUN cana-844 369 12 31 31 NUM cana-844 369 13 no no NOUN cana-844 369 14 . . PUNCT cana-844 370 1 4s 4s NUM cana-844 370 2 ( ( PUNCT cana-844 370 3 2024 2024 NUM cana-844 370 4 ) ) PUNCT cana-844 370 5 252 252 NUM cana-844 370 6 https://internationalpubls.com https://internationalpubls.com X cana-844 371 1 [ [ X cana-844 371 2 13 13 NUM cana-844 371 3 ] ] PUNCT cana-844 371 4 s. s. PROPN cana-844 371 5 a. a. PROPN cana-844 371 6 qureshi qureshi PROPN cana-844 371 7 et et PROPN cana-844 371 8 al al PROPN cana-844 371 9 . . PROPN cana-844 371 10 , , PUNCT cana-844 371 11 β€œ " PUNCT cana-844 371 12 radiogenomic radiogenomic ADJ cana-844 371 13 classification classification NOUN cana-844 371 14 for for ADP cana-844 371 15 mgmt mgmt NOUN cana-844 371 16 promoter promoter NOUN cana-844 371 17 methylation methylation NOUN cana-844 371 18 status status NOUN cana-844 371 19 using use VERB cana-844 371 20 multi multi ADJ cana-844 371 21 - - ADJ cana-844 371 22 omics omics ADJ cana-844 371 23 fused fuse VERB cana-844 371 24 feature feature NOUN cana-844 371 25 space space NOUN cana-844 371 26 for for ADP cana-844 371 27 least least ADJ cana-844 371 28 invasive invasive ADJ cana-844 371 29 diagnosis diagnosis NOUN cana-844 371 30 through through ADP cana-844 371 31 mpmri mpmri PROPN cana-844 371 32 scans scan NOUN cana-844 371 33 , , PUNCT cana-844 371 34 ” " PUNCT cana-844 371 35 scientific scientific ADJ cana-844 371 36 reports report NOUN cana-844 371 37 , , PUNCT cana-844 371 38 vol vol NOUN cana-844 371 39 . . PROPN cana-844 371 40 13 13 NUM cana-844 371 41 , , PUNCT cana-844 371 42 no no INTJ cana-844 371 43 . . NOUN cana-844 371 44 1 1 NUM cana-844 371 45 , , PUNCT cana-844 371 46 feb feb PROPN cana-844 371 47 . . PROPN cana-844 371 48 2023 2023 NUM cana-844 371 49 , , PUNCT cana-844 371 50 doi doi NOUN cana-844 371 51 : : PUNCT cana-844 371 52 10.1038 10.1038 NUM cana-844 371 53 / / SYM cana-844 371 54 s41598 s41598 NOUN cana-844 371 55 - - PUNCT cana-844 371 56 023 023 NUM cana-844 371 57 - - PUNCT cana-844 371 58 30309 30309 NUM cana-844 371 59 - - SYM cana-844 371 60 4 4 NUM cana-844 371 61 . . PUNCT cana-844 372 1 [ [ X cana-844 372 2 14 14 NUM cana-844 372 3 ] ] X cana-844 372 4 l. l. PROPN cana-844 372 5 robinet robinet PROPN cana-844 372 6 , , PUNCT cana-844 372 7 a. a. PROPN cana-844 372 8 siegfried siegfried PROPN cana-844 372 9 , , PUNCT cana-844 372 10 m. m. NOUN cana-844 372 11 roques roque NOUN cana-844 372 12 , , PUNCT cana-844 372 13 a. a. NOUN cana-844 372 14 berjaoui berjaoui PROPN cana-844 372 15 , , PUNCT cana-844 372 16 and and CCONJ cana-844 372 17 e. e. PROPN cana-844 372 18 c.-j c.-j PROPN cana-844 372 19 . . PUNCT cana-844 373 1 moyal moyal PROPN cana-844 373 2 , , PUNCT cana-844 373 3 β€œ " PUNCT cana-844 373 4 mri mri NOUN cana-844 373 5 - - PUNCT cana-844 373 6 based base VERB cana-844 373 7 deep deep ADJ cana-844 373 8 learning learning NOUN cana-844 373 9 tools tool NOUN cana-844 373 10 for for ADP cana-844 373 11 mgmt mgmt NOUN cana-844 373 12 promoter promoter NOUN cana-844 373 13 methylation methylation NOUN cana-844 373 14 detection detection NOUN cana-844 373 15 : : PUNCT cana-844 373 16 a a DET cana-844 373 17 thorough thorough ADJ cana-844 373 18 evaluation evaluation NOUN cana-844 373 19 , , PUNCT cana-844 373 20 ” " PUNCT cana-844 373 21 cancers cancer NOUN cana-844 373 22 , , PUNCT cana-844 373 23 vol vol NOUN cana-844 373 24 . . PROPN cana-844 373 25 15 15 NUM cana-844 373 26 , , PUNCT cana-844 373 27 no no INTJ cana-844 373 28 . . NOUN cana-844 373 29 8 8 NUM cana-844 373 30 , , PUNCT cana-844 373 31 p. p. NOUN cana-844 373 32 2253 2253 NUM cana-844 373 33 , , PUNCT cana-844 373 34 apr apr PROPN cana-844 373 35 . . PROPN cana-844 373 36 2023 2023 NUM cana-844 373 37 , , PUNCT cana-844 373 38 doi doi NOUN cana-844 373 39 : : PUNCT cana-844 373 40 10.3390 10.3390 NUM cana-844 373 41 / / SYM cana-844 373 42 cancers15082253 cancers15082253 PROPN cana-844 373 43 . . PUNCT cana-844 374 1 [ [ X cana-844 374 2 15 15 NUM cana-844 374 3 ] ] X cana-844 374 4 f. f. PROPN cana-844 374 5 kamalov kamalov PROPN cana-844 374 6 , , PUNCT cana-844 374 7 h. h. PROPN cana-844 374 8 -h -h PROPN cana-844 374 9 . . PROPN cana-844 374 10 leung leung PROPN cana-844 374 11 and and CCONJ cana-844 374 12 a. a. PROPN cana-844 374 13 k. k. PROPN cana-844 374 14 cherukuri cherukuri PROPN cana-844 374 15 , , PUNCT cana-844 374 16 " " PUNCT cana-844 374 17 keep keep VERB cana-844 374 18 it it PRON cana-844 374 19 simple simple ADJ cana-844 374 20 : : PUNCT cana-844 374 21 random random ADJ cana-844 374 22 oversampling oversampling NOUN cana-844 374 23 for for ADP cana-844 374 24 imbalanced imbalanced ADJ cana-844 374 25 data datum NOUN cana-844 374 26 , , PUNCT cana-844 374 27 " " PUNCT cana-844 374 28 2023 2023 NUM cana-844 374 29 advances advance NOUN cana-844 374 30 in in ADP cana-844 374 31 science science NOUN cana-844 374 32 and and CCONJ cana-844 374 33 engineering engineering NOUN cana-844 374 34 technology technology NOUN cana-844 374 35 international international ADJ cana-844 374 36 conferences conference NOUN cana-844 374 37 ( ( PUNCT cana-844 374 38 aset aset NOUN cana-844 374 39 ) ) PUNCT cana-844 374 40 , , PUNCT cana-844 374 41 dubai dubai PROPN cana-844 374 42 , , PUNCT cana-844 374 43 united united PROPN cana-844 374 44 arab arab PROPN cana-844 374 45 emirates emirates PROPN cana-844 374 46 , , PUNCT cana-844 374 47 2023 2023 NUM cana-844 374 48 , , PUNCT cana-844 374 49 pp pp ADJ cana-844 374 50 . . PUNCT cana-844 375 1 1 1 NUM cana-844 375 2 - - SYM cana-844 375 3 4 4 NUM cana-844 375 4 , , PUNCT cana-844 375 5 doi doi NOUN cana-844 375 6 : : PUNCT cana-844 375 7 10.1109 10.1109 NUM cana-844 375 8 / / SYM cana-844 375 9 aset56582.2023.10180891 aset56582.2023.10180891 NOUN cana-844 375 10 . . PUNCT cana-844 376 1 [ [ X cana-844 376 2 16 16 NUM cana-844 376 3 ] ] PUNCT cana-844 376 4 m. m. NOUN cana-844 376 5 a. a. PROPN cana-844 376 6 khan khan PROPN cana-844 376 7 et et PROPN cana-844 376 8 al al PROPN cana-844 376 9 . . PROPN cana-844 376 10 , , PUNCT cana-844 376 11 β€œ " PUNCT cana-844 376 12 multimodal multimodal ADJ cana-844 376 13 brain brain NOUN cana-844 376 14 tumor tumor NOUN cana-844 376 15 classification classification NOUN cana-844 376 16 using use VERB cana-844 376 17 deep deep ADJ cana-844 376 18 learning learning NOUN cana-844 376 19 and and CCONJ cana-844 376 20 robust robust ADJ cana-844 376 21 feature feature NOUN cana-844 376 22 selection selection NOUN cana-844 376 23 : : PUNCT cana-844 376 24 a a DET cana-844 376 25 machine machine NOUN cana-844 376 26 learning learn VERB cana-844 376 27 application application NOUN cana-844 376 28 for for ADP cana-844 376 29 radiologists radiologist NOUN cana-844 376 30 , , PUNCT cana-844 376 31 ” " PUNCT cana-844 376 32 diagnostics diagnostic NOUN cana-844 376 33 , , PUNCT cana-844 376 34 vol vol NOUN cana-844 376 35 . . PROPN cana-844 377 1 10 10 NUM cana-844 377 2 , , PUNCT cana-844 377 3 no no INTJ cana-844 377 4 . . NOUN cana-844 377 5 8 8 NUM cana-844 377 6 , , PUNCT cana-844 377 7 p. p. NOUN cana-844 377 8 565 565 NUM cana-844 377 9 , , PUNCT cana-844 377 10 aug aug PROPN cana-844 377 11 . . PROPN cana-844 377 12 2020 2020 NUM cana-844 377 13 , , PUNCT cana-844 377 14 doi doi NOUN cana-844 377 15 : : PUNCT cana-844 377 16 10.3390 10.3390 NUM cana-844 377 17 / / SYM cana-844 377 18 diagnostics10080565 diagnostics10080565 PROPN cana-844 377 19 . . PUNCT cana-844 378 1 [ [ X cana-844 378 2 17 17 NUM cana-844 378 3 ] ] PUNCT cana-844 378 4 mathivanan mathivanan NOUN cana-844 378 5 , , PUNCT cana-844 378 6 s.k s.k PROPN cana-844 378 7 . . PROPN cana-844 378 8 , , PUNCT cana-844 378 9 sonaimuthu sonaimuthu PROPN cana-844 378 10 , , PUNCT cana-844 378 11 s. s. PROPN cana-844 378 12 , , PUNCT cana-844 378 13 murugesan murugesan PROPN cana-844 378 14 , , PUNCT cana-844 378 15 s. s. PROPN cana-844 378 16 et et PROPN cana-844 378 17 al al PROPN cana-844 378 18 . . PUNCT cana-844 379 1 employing employ VERB cana-844 379 2 deep deep ADJ cana-844 379 3 learning learning NOUN cana-844 379 4 and and CCONJ cana-844 379 5 transfer transfer VERB cana-844 379 6 learning learning NOUN cana-844 379 7 for for ADP cana-844 379 8 accurate accurate ADJ cana-844 379 9 brain brain NOUN cana-844 379 10 tumor tumor NOUN cana-844 379 11 detection detection NOUN cana-844 379 12 . . PUNCT cana-844 380 1 sci sci PROPN cana-844 380 2 rep rep PROPN cana-844 380 3 14 14 NUM cana-844 380 4 , , PUNCT cana-844 380 5 7232 7232 NUM cana-844 380 6 ( ( PUNCT cana-844 380 7 2024 2024 NUM cana-844 380 8 ) ) PUNCT cana-844 380 9 . . PUNCT cana-844 381 1 https://doi.org/10.1038/s41598-024-57970-7 https://doi.org/10.1038/s41598-024-57970-7 NUM cana-844 382 1 [ [ X cana-844 382 2 18 18 NUM cana-844 382 3 ] ] PUNCT cana-844 382 4 he he PRON cana-844 382 5 , , PUNCT cana-844 382 6 k. k. PROPN cana-844 382 7 ; ; PUNCT cana-844 382 8 zhang zhang PROPN cana-844 382 9 , , PUNCT cana-844 382 10 x. x. PROPN cana-844 382 11 ; ; PUNCT cana-844 382 12 ren ren PROPN cana-844 382 13 , , PUNCT cana-844 382 14 s. s. PROPN cana-844 382 15 ; ; PUNCT cana-844 382 16 sun sun PROPN cana-844 382 17 , , PUNCT cana-844 382 18 j. j. PROPN cana-844 382 19 deep deep ADJ cana-844 382 20 residual residual ADJ cana-844 382 21 learning learning NOUN cana-844 382 22 for for ADP cana-844 382 23 image image NOUN cana-844 382 24 recognition recognition NOUN cana-844 382 25 . . PUNCT cana-844 383 1 in in ADP cana-844 383 2 proceedings proceeding NOUN cana-844 383 3 of of ADP cana-844 383 4 the the DET cana-844 383 5 ieee ieee NOUN cana-844 383 6 conference conference NOUN cana-844 383 7 on on ADP cana-844 383 8 computer computer NOUN cana-844 383 9 vision vision NOUN cana-844 383 10 and and CCONJ cana-844 383 11 pattern pattern NOUN cana-844 383 12 recognition recognition NOUN cana-844 383 13 , , PUNCT cana-844 383 14 las las PROPN cana-844 383 15 vegas vegas PROPN cana-844 383 16 , , PUNCT cana-844 383 17 nv nv PROPN cana-844 383 18 , , PUNCT cana-844 383 19 usa usa PROPN cana-844 383 20 , , PUNCT cana-844 383 21 27–30 27–30 NUM cana-844 383 22 june june PROPN cana-844 383 23 2016 2016 NUM cana-844 383 24 ; ; PUNCT cana-844 383 25 pp pp ADP cana-844 383 26 . . PUNCT cana-844 384 1 770–778 770–778 NUM cana-844 384 2 . . PUNCT cana-844 385 1 [ [ X cana-844 385 2 19 19 NUM cana-844 385 3 ] ] X cana-844 385 4 w. w. PROPN cana-844 385 5 islam islam PROPN cana-844 385 6 , , PUNCT cana-844 385 7 m. m. PROPN cana-844 385 8 jones jones PROPN cana-844 385 9 , , PUNCT cana-844 385 10 r. r. PROPN cana-844 385 11 faiz faiz PROPN cana-844 385 12 , , PUNCT cana-844 385 13 n. n. PROPN cana-844 385 14 sadeghipour sadeghipour NOUN cana-844 385 15 , , PUNCT cana-844 385 16 y. y. PROPN cana-844 385 17 qiu qiu PROPN cana-844 385 18 , , PUNCT cana-844 385 19 and and CCONJ cana-844 385 20 b. b. PROPN cana-844 385 21 zheng zheng PROPN cana-844 385 22 , , PUNCT cana-844 385 23 β€œ " PUNCT cana-844 385 24 improving improve VERB cana-844 385 25 performance performance NOUN cana-844 385 26 of of ADP cana-844 385 27 breast breast NOUN cana-844 385 28 lesion lesion NOUN cana-844 385 29 classification classification NOUN cana-844 385 30 using use VERB cana-844 385 31 a a DET cana-844 385 32 resnet50 resnet50 NOUN cana-844 385 33 model model NOUN cana-844 385 34 optimized optimize VERB cana-844 385 35 with with ADP cana-844 385 36 a a DET cana-844 385 37 novel novel ADJ cana-844 385 38 attention attention NOUN cana-844 385 39 mechanism mechanism NOUN cana-844 385 40 , , PUNCT cana-844 385 41 ” " PUNCT cana-844 385 42 tomography tomography NOUN cana-844 385 43 , , PUNCT cana-844 385 44 vol vol NOUN cana-844 385 45 . . PROPN cana-844 385 46 8 8 NUM cana-844 385 47 , , PUNCT cana-844 385 48 no no INTJ cana-844 385 49 . . NOUN cana-844 385 50 5 5 NUM cana-844 385 51 , , PUNCT cana-844 385 52 pp pp ADJ cana-844 385 53 . . PUNCT cana-844 386 1 2411–2425 2411–2425 NUM cana-844 386 2 , , PUNCT cana-844 386 3 sep sep PROPN cana-844 386 4 . . PROPN cana-844 386 5 2022 2022 NUM cana-844 386 6 , , PUNCT cana-844 386 7 doi doi NOUN cana-844 386 8 : : PUNCT cana-844 386 9 10.3390 10.3390 NUM cana-844 386 10 / / SYM cana-844 386 11 tomography8050200 tomography8050200 PROPN cana-844 386 12 . . PUNCT cana-844 387 1 [ [ X cana-844 387 2 20 20 NUM cana-844 387 3 ] ] X cana-844 387 4 iranzad iranzad PROPN cana-844 387 5 , , PUNCT cana-844 387 6 r. r. PROPN cana-844 387 7 , , PUNCT cana-844 387 8 liu liu PROPN cana-844 387 9 , , PUNCT cana-844 387 10 x. x. VERB cana-844 387 11 a a DET cana-844 387 12 review review NOUN cana-844 387 13 of of ADP cana-844 387 14 random random ADJ cana-844 387 15 forest forest NOUN cana-844 387 16 - - PUNCT cana-844 387 17 based base VERB cana-844 387 18 feature feature NOUN cana-844 387 19 selection selection NOUN cana-844 387 20 methods method NOUN cana-844 387 21 for for ADP cana-844 387 22 data datum NOUN cana-844 387 23 science science NOUN cana-844 387 24 education education NOUN cana-844 387 25 and and CCONJ cana-844 387 26 applications application NOUN cana-844 387 27 . . PUNCT cana-844 388 1 int int PROPN cana-844 388 2 j j PROPN cana-844 388 3 data data PROPN cana-844 388 4 sci sci PROPN cana-844 388 5 anal anal PROPN cana-844 388 6 ( ( PUNCT cana-844 388 7 2024 2024 NUM cana-844 388 8 ) ) PUNCT cana-844 388 9 . . PUNCT cana-844 389 1 https://doi.org/10.1007/s41060-024-00509-w https://doi.org/10.1007/s41060-024-00509-w NOUN cana-844 389 2 . . PUNCT cana-844 390 1 [ [ X cana-844 390 2 21 21 NUM cana-844 390 3 ] ] PUNCT cana-844 390 4 s. s. PROPN cana-844 390 5 uddin uddin PROPN cana-844 390 6 , , PUNCT cana-844 390 7 i. i. PROPN cana-844 390 8 haque haque PROPN cana-844 390 9 , , PUNCT cana-844 390 10 h. h. PROPN cana-844 390 11 lu lu PROPN cana-844 390 12 , , PUNCT cana-844 390 13 m. m. NOUN cana-844 390 14 a. a. NOUN cana-844 390 15 moni moni PROPN cana-844 390 16 , , PUNCT cana-844 390 17 and and CCONJ cana-844 390 18 e. e. PROPN cana-844 390 19 gide gide PROPN cana-844 390 20 , , PUNCT cana-844 390 21 β€œ " PUNCT cana-844 390 22 comparative comparative ADJ cana-844 390 23 performance performance NOUN cana-844 390 24 analysis analysis NOUN cana-844 390 25 of of ADP cana-844 390 26 k k NOUN cana-844 390 27 - - PUNCT cana-844 390 28 nearest near ADJ cana-844 390 29 neighbour neighbour NOUN cana-844 390 30 ( ( PUNCT cana-844 390 31 knn knn PROPN cana-844 390 32 ) ) PUNCT cana-844 390 33 algorithm algorithm NOUN cana-844 390 34 and and CCONJ cana-844 390 35 its its PRON cana-844 390 36 different different ADJ cana-844 390 37 variants variant NOUN cana-844 390 38 for for ADP cana-844 390 39 disease disease NOUN cana-844 390 40 prediction prediction NOUN cana-844 390 41 , , PUNCT cana-844 390 42 ” " PUNCT cana-844 390 43 scientific scientific ADJ cana-844 390 44 reports report NOUN cana-844 390 45 , , PUNCT cana-844 390 46 vol vol NOUN cana-844 390 47 . . PROPN cana-844 390 48 12 12 NUM cana-844 390 49 , , PUNCT cana-844 390 50 no no INTJ cana-844 390 51 . . NOUN cana-844 390 52 1 1 NUM cana-844 390 53 , , PUNCT cana-844 390 54 apr apr NOUN cana-844 390 55 . . PROPN cana-844 390 56 2022 2022 NUM cana-844 390 57 , , PUNCT cana-844 390 58 doi doi NOUN cana-844 390 59 : : PUNCT cana-844 390 60 10.1038 10.1038 NUM cana-844 390 61 / / SYM cana-844 390 62 s41598 s41598 NOUN cana-844 390 63 - - PUNCT cana-844 390 64 022 022 NUM cana-844 390 65 - - PUNCT cana-844 390 66 10358 10358 NUM cana-844 390 67 - - PUNCT cana-844 390 68 x. x. NOUN cana-844 391 1 [ [ X cana-844 391 2 22 22 NUM cana-844 391 3 ] ] X cana-844 391 4 venkatesh venkatesh NOUN cana-844 391 5 and and CCONJ cana-844 391 6 m. m. PROPN cana-844 391 7 leo leo PROPN cana-844 391 8 , , PUNCT cana-844 391 9 β€œ " PUNCT cana-844 391 10 mri mri NOUN cana-844 391 11 brain brain NOUN cana-844 391 12 image image NOUN cana-844 391 13 segmentation segmentation NOUN cana-844 391 14 and and CCONJ cana-844 391 15 detection detection NOUN cana-844 391 16 using use VERB cana-844 391 17 k k PROPN cana-844 391 18 - - PUNCT cana-844 391 19 nn nn ADJ cana-844 391 20 classification classification NOUN cana-844 391 21 , , PUNCT cana-844 391 22 ” " PUNCT cana-844 391 23 journal journal NOUN cana-844 391 24 of of ADP cana-844 391 25 physics physics PROPN cana-844 391 26 : : PUNCT cana-844 391 27 conference conference NOUN cana-844 391 28 series series NOUN cana-844 391 29 , , PUNCT cana-844 391 30 vol vol NOUN cana-844 391 31 . . PROPN cana-844 391 32 1362 1362 NUM cana-844 391 33 , , PUNCT cana-844 391 34 no no INTJ cana-844 391 35 . . NOUN cana-844 391 36 1 1 NUM cana-844 391 37 , , PUNCT cana-844 391 38 p. p. NOUN cana-844 391 39 012073 012073 NUM cana-844 391 40 , , PUNCT cana-844 391 41 nov nov PROPN cana-844 391 42 . . PROPN cana-844 391 43 2019 2019 NUM cana-844 391 44 , , PUNCT cana-844 391 45 doi doi NOUN cana-844 391 46 : : PUNCT cana-844 391 47 10.1088/1742 10.1088/1742 NUM cana-844 391 48 - - SYM cana-844 391 49 6596/1362/1/01207 6596/1362/1/01207 NOUN cana-844 391 50 . . PUNCT cana-844 392 1 [ [ X cana-844 392 2 23 23 NUM cana-844 392 3 ] ] X cana-844 392 4 v. v. CCONJ cana-844 392 5 sheth sheth PROPN cana-844 392 6 , , PUNCT cana-844 392 7 u. u. PROPN cana-844 392 8 tripathi tripathi PROPN cana-844 392 9 , , PUNCT cana-844 392 10 and and CCONJ cana-844 392 11 a. a. NOUN cana-844 392 12 sharma sharma PROPN cana-844 392 13 , , PUNCT cana-844 392 14 β€œ " PUNCT cana-844 392 15 a a DET cana-844 392 16 comparative comparative ADJ cana-844 392 17 analysis analysis NOUN cana-844 392 18 of of ADP cana-844 392 19 machine machine NOUN cana-844 392 20 learning learn VERB cana-844 392 21 algorithms algorithm NOUN cana-844 392 22 for for ADP cana-844 392 23 classification classification NOUN cana-844 392 24 purpose purpose NOUN cana-844 392 25 , , PUNCT cana-844 392 26 ” " PUNCT cana-844 392 27 procedia procedia NOUN cana-844 392 28 computer computer NOUN cana-844 392 29 science science NOUN cana-844 392 30 , , PUNCT cana-844 392 31 vol vol NOUN cana-844 392 32 . . PROPN cana-844 392 33 215 215 NUM cana-844 392 34 , , PUNCT cana-844 392 35 pp pp ADJ cana-844 392 36 . . PUNCT cana-844 393 1 422–431 422–431 NUM cana-844 393 2 , , PUNCT cana-844 393 3 jan jan PROPN cana-844 393 4 . . PROPN cana-844 393 5 2022 2022 NUM cana-844 393 6 , , PUNCT cana-844 393 7 doi doi NOUN cana-844 393 8 : : PUNCT cana-844 393 9 10.1016 10.1016 NUM cana-844 393 10 / / SYM cana-844 393 11 j.procs.2022.12.044 j.procs.2022.12.044 PROPN cana-844 393 12 . . PUNCT cana-844 394 1 [ [ X cana-844 394 2 24 24 NUM cana-844 394 3 ] ] X cana-844 394 4 v. v. ADP cana-844 394 5 jackins jackin NOUN cana-844 394 6 , , PUNCT cana-844 394 7 s. s. PROPN cana-844 394 8 vimal vimal PROPN cana-844 394 9 , , PUNCT cana-844 394 10 m. m. NOUN cana-844 394 11 kaliappan kaliappan NOUN cana-844 394 12 , , PUNCT cana-844 394 13 and and CCONJ cana-844 394 14 m. m. PROPN cana-844 394 15 y. y. PROPN cana-844 394 16 lee lee PROPN cana-844 394 17 , , PUNCT cana-844 394 18 β€œ " PUNCT cana-844 394 19 ai ai VERB cana-844 394 20 - - PUNCT cana-844 394 21 based base VERB cana-844 394 22 smart smart ADJ cana-844 394 23 prediction prediction NOUN cana-844 394 24 of of ADP cana-844 394 25 clinical clinical ADJ cana-844 394 26 disease disease NOUN cana-844 394 27 using use VERB cana-844 394 28 random random ADJ cana-844 394 29 forest forest NOUN cana-844 394 30 classifier classifier NOUN cana-844 394 31 and and CCONJ cana-844 394 32 naive naive ADJ cana-844 394 33 bayes bayes NOUN cana-844 394 34 , , PUNCT cana-844 394 35 ” " PUNCT cana-844 394 36 the the DET cana-844 394 37 journal journal NOUN cana-844 394 38 of of ADP cana-844 394 39 supercomputing supercomputing NOUN cana-844 394 40 , , PUNCT cana-844 394 41 vol vol NOUN cana-844 394 42 . . PROPN cana-844 395 1 77 77 NUM cana-844 395 2 , , PUNCT cana-844 395 3 no no INTJ cana-844 395 4 . . NOUN cana-844 395 5 5 5 NUM cana-844 395 6 , , PUNCT cana-844 395 7 pp pp ADJ cana-844 395 8 . . PUNCT cana-844 396 1 5198–5219 5198–5219 NUM cana-844 396 2 , , PUNCT cana-844 396 3 nov nov PROPN cana-844 396 4 . . PROPN cana-844 396 5 2020 2020 NUM cana-844 396 6 , , PUNCT cana-844 396 7 doi doi NOUN cana-844 396 8 : : PUNCT cana-844 396 9 10.1007 10.1007 NUM cana-844 396 10 / / SYM cana-844 396 11 s11227 s11227 VERB cana-844 396 12 - - PUNCT cana-844 396 13 020 020 NUM cana-844 396 14 - - PUNCT cana-844 396 15 03481 03481 NUM cana-844 396 16 - - PUNCT cana-844 396 17 x. x. NOUN cana-844 397 1 [ [ X cana-844 397 2 25 25 NUM cana-844 397 3 ] ] PUNCT cana-844 397 4 k. k. PROPN cana-844 397 5 sumwiza sumwiza PROPN cana-844 397 6 , , PUNCT cana-844 397 7 c. c. PROPN cana-844 397 8 twizere twizere PROPN cana-844 397 9 , , PUNCT cana-844 397 10 g. g. PROPN cana-844 397 11 rushingabigwi rushingabigwi PROPN cana-844 397 12 , , PUNCT cana-844 397 13 p. p. NOUN cana-844 397 14 bakunzibake bakunzibake NOUN cana-844 397 15 , , PUNCT cana-844 397 16 and and CCONJ cana-844 397 17 p. p. NOUN cana-844 397 18 bamurigire bamurigire NOUN cana-844 397 19 , , PUNCT cana-844 397 20 β€œ " PUNCT cana-844 397 21 enhanced enhance VERB cana-844 397 22 cardiovascular cardiovascular ADJ cana-844 397 23 disease disease NOUN cana-844 397 24 prediction prediction NOUN cana-844 397 25 model model NOUN cana-844 397 26 using use VERB cana-844 397 27 random random ADJ cana-844 397 28 forest forest NOUN cana-844 397 29 algorithm algorithm NOUN cana-844 397 30 , , PUNCT cana-844 397 31 ” " PUNCT cana-844 397 32 informatics informatic NOUN cana-844 397 33 in in ADP cana-844 397 34 medicine medicine NOUN cana-844 397 35 unlocked unlock VERB cana-844 397 36 , , PUNCT cana-844 397 37 vol vol NOUN cana-844 397 38 . . PROPN cana-844 397 39 41 41 NUM cana-844 397 40 , , PUNCT cana-844 397 41 p. p. NOUN cana-844 397 42 101316 101316 NUM cana-844 397 43 , , PUNCT cana-844 397 44 jan jan PROPN cana-844 397 45 . . PROPN cana-844 397 46 2023 2023 NUM cana-844 397 47 , , PUNCT cana-844 397 48 doi doi NOUN cana-844 397 49 : : PUNCT cana-844 397 50 10.1016 10.1016 NUM cana-844 397 51 / / SYM cana-844 397 52 j.imu.2023.101316 j.imu.2023.101316 PROPN cana-844 397 53 . . PUNCT cana-844 398 1 [ [ X cana-844 398 2 26 26 NUM cana-844 398 3 ] ] PUNCT cana-844 398 4 p. p. NOUN cana-844 398 5 schober schober PROPN cana-844 398 6 and and CCONJ cana-844 398 7 t. t. PROPN cana-844 398 8 r. r. PROPN cana-844 398 9 vetter vetter PROPN cana-844 398 10 , , PUNCT cana-844 398 11 β€œ " PUNCT cana-844 398 12 logistic logistic ADJ cana-844 398 13 regression regression NOUN cana-844 398 14 in in ADP cana-844 398 15 medical medical ADJ cana-844 398 16 research research NOUN cana-844 398 17 , , PUNCT cana-844 398 18 ” " PUNCT cana-844 398 19 anesthesia anesthesia PROPN cana-844 398 20 & & CCONJ cana-844 398 21 analgesia analgesia PROPN cana-844 398 22 , , PUNCT cana-844 398 23 vol vol NOUN cana-844 398 24 . . PROPN cana-844 398 25 132 132 NUM cana-844 398 26 , , PUNCT cana-844 398 27 no no INTJ cana-844 398 28 . . NOUN cana-844 398 29 2 2 NUM cana-844 398 30 , , PUNCT cana-844 398 31 pp pp ADJ cana-844 398 32 . . PUNCT cana-844 399 1 365–366 365–366 NUM cana-844 399 2 , , PUNCT cana-844 399 3 jan jan PROPN cana-844 399 4 . . PROPN cana-844 399 5 2021 2021 NUM cana-844 399 6 , , PUNCT cana-844 399 7 doi doi NOUN cana-844 399 8 : : PUNCT cana-844 399 9 10.1213 10.1213 NUM cana-844 399 10 / / SYM cana-844 399 11 ane.0000000000005247 ane.0000000000005247 NOUN cana-844 399 12 . . PUNCT cana-844 400 1 [ [ X cana-844 400 2 27 27 NUM cana-844 400 3 ] ] X cana-844 400 4 s. s. PROPN cana-844 400 5 jain jain PROPN cana-844 400 6 , , PUNCT cana-844 400 7 β€œ " PUNCT cana-844 400 8 brain brain NOUN cana-844 400 9 cancer cancer NOUN cana-844 400 10 classification classification NOUN cana-844 400 11 using use VERB cana-844 400 12 glcm glcm NOUN cana-844 400 13 based base VERB cana-844 400 14 feature feature NOUN cana-844 400 15 extraction extraction NOUN cana-844 400 16 in in ADP cana-844 400 17 artificial artificial ADJ cana-844 400 18 neural neural ADJ cana-844 400 19 network network NOUN cana-844 400 20 , , PUNCT cana-844 400 21 ” " PUNCT cana-844 400 22 international international ADJ cana-844 400 23 journal journal NOUN cana-844 400 24 of of ADP cana-844 400 25 computer computer NOUN cana-844 400 26 science science PROPN cana-844 400 27 & & CCONJ cana-844 400 28 engineering engineering PROPN cana-844 400 29 technology technology NOUN cana-844 400 30 , , PUNCT cana-844 400 31 jan jan PROPN cana-844 400 32 . . PROPN cana-844 400 33 2013 2013 NUM cana-844 400 34 , , PUNCT cana-844 401 1 [ [ X cana-844 401 2 online online X cana-844 401 3 ] ] X cana-844 401 4 . . PUNCT cana-844 402 1 available available ADJ cana-844 402 2 : : PUNCT cana-844 403 1 http://www.ijcset.com/docs/ijcset13-04-07-077.pdf http://www.ijcset.com/docs/ijcset13-04-07-077.pdf NOUN cana-844 404 1 [ [ X cana-844 404 2 28 28 NUM cana-844 404 3 ] ] X cana-844 404 4 m. m. NOUN cana-844 404 5 dehmer dehmer NOUN cana-844 404 6 and and CCONJ cana-844 404 7 s. s. PROPN cana-844 404 8 c. c. PROPN cana-844 404 9 basak basak PROPN cana-844 404 10 , , PUNCT cana-844 404 11 statistical statistical ADJ cana-844 404 12 and and CCONJ cana-844 404 13 machine machine NOUN cana-844 404 14 learning learning NOUN cana-844 404 15 approaches approach NOUN cana-844 404 16 for for ADP cana-844 404 17 network network NOUN cana-844 404 18 analysis analysis NOUN cana-844 404 19 . . PUNCT cana-844 405 1 2012 2012 NUM cana-844 405 2 . . PUNCT cana-844 406 1 doi doi NOUN cana-844 406 2 : : PUNCT cana-844 406 3 10.1002/9781118346990 10.1002/9781118346990 NUM cana-844 406 4 . . PUNCT cana-844 407 1 [ [ X cana-844 407 2 29 29 NUM cana-844 407 3 ] ] SYM cana-844 407 4 emmert emmert NOUN cana-844 407 5 - - PUNCT cana-844 407 6 streib streib PROPN cana-844 407 7 , , PUNCT cana-844 407 8 f. f. PROPN cana-844 407 9 , , PUNCT cana-844 407 10 moutari moutari PROPN cana-844 407 11 , , PUNCT cana-844 407 12 s. s. PROPN cana-844 407 13 & & CCONJ cana-844 407 14 dehmer dehmer PROPN cana-844 407 15 , , PUNCT cana-844 407 16 m. m. NOUN cana-844 407 17 elements element NOUN cana-844 407 18 of of ADP cana-844 407 19 data datum NOUN cana-844 407 20 science science NOUN cana-844 407 21 , , PUNCT cana-844 407 22 machine machine NOUN cana-844 407 23 learning learning NOUN cana-844 407 24 , , PUNCT cana-844 407 25 and and CCONJ cana-844 407 26 artifcial artifcial ADJ cana-844 407 27 intelligence intelligence NOUN cana-844 407 28 using use VERB cana-844 407 29 r r NOUN cana-844 407 30 ( ( PUNCT cana-844 407 31 springer springer NOUN cana-844 407 32 , , PUNCT cana-844 407 33 2023 2023 NUM cana-844 407 34 ) ) PUNCT cana-844 407 35 . . PUNCT cana-844 408 1 [ [ X cana-844 408 2 30 30 NUM cana-844 408 3 ] ] PUNCT cana-844 408 4 s. s. PROPN cana-844 408 5 k. k. PROPN cana-844 408 6 a. a. PROPN cana-844 408 7 secure secure PROPN cana-844 408 8 algorithm algorithm NOUN cana-844 408 9 for for ADP cana-844 408 10 file file NOUN cana-844 408 11 sharing sharing NOUN cana-844 408 12 using use VERB cana-844 408 13 clustering clustering ADJ cana-844 408 14 technique technique NOUN cana-844 408 15 of of ADP cana-844 408 16 k k NOUN cana-844 408 17 - - PUNCT cana-844 408 18 means means NOUN cana-844 408 19 clustering clustering NOUN cana-844 408 20 . . PUNCT cana-844 409 1 ijritcc ijritcc ADJ cana-844 409 2 2016 2016 NUM cana-844 409 3 , , PUNCT cana-844 409 4 4 4 NUM cana-844 409 5 , , PUNCT cana-844 409 6 35 35 NUM cana-844 409 7 - - SYM cana-844 409 8 39 39 NUM cana-844 409 9 . . PUNCT cana-844 410 1 [ [ X cana-844 410 2 31 31 NUM cana-844 410 3 ] ] PUNCT cana-844 410 4 satish satish PROPN cana-844 410 5 kumar kumar PROPN cana-844 410 6 alaria alaria PROPN cana-844 410 7 and and CCONJ cana-844 410 8 abha abha VERB cana-844 410 9 jadaun jadaun ADJ cana-844 410 10 . . PUNCT cana-844 411 1 β€œ " PUNCT cana-844 411 2 design design NOUN cana-844 411 3 and and CCONJ cana-844 411 4 performance performance NOUN cana-844 411 5 assessment assessment NOUN cana-844 411 6 of of ADP cana-844 411 7 light light ADJ cana-844 411 8 weight weight NOUN cana-844 411 9 data data NOUN cana-844 411 10 security security NOUN cana-844 411 11 system system NOUN cana-844 411 12 for for ADP cana-844 411 13 secure secure ADJ cana-844 411 14 data datum NOUN cana-844 411 15 transmission transmission NOUN cana-844 411 16 in in ADP cana-844 411 17 iot iot NOUN cana-844 411 18 ” " PUNCT cana-844 411 19 , , PUNCT cana-844 411 20 journal journal NOUN cana-844 411 21 of of ADP cana-844 411 22 network network NOUN cana-844 411 23 security security NOUN cana-844 411 24 , , PUNCT cana-844 411 25 2021 2021 NUM cana-844 411 26 , , PUNCT cana-844 411 27 vol-9 vol-9 X cana-844 411 28 , , PUNCT cana-844 411 29 issue-1 issue-1 X cana-844 411 30 , , PUNCT cana-844 411 31 pp pp PRON cana-844 411 32 : : PUNCT cana-844 411 33 29 29 NUM cana-844 411 34 - - SYM cana-844 411 35 41 41 NUM cana-844 411 36 . . PUNCT cana-844 412 1 [ [ X cana-844 412 2 32 32 NUM cana-844 412 3 ] ] PUNCT cana-844 412 4 pratiksha pratiksha PROPN cana-844 412 5 mishra mishra PROPN cana-844 412 6 satish satish PROPN cana-844 412 7 kumar kumar PROPN cana-844 412 8 alaria alaria PROPN cana-844 412 9 . . PUNCT cana-844 413 1 β€œ " PUNCT cana-844 413 2 design design NOUN cana-844 413 3 & & CCONJ cana-844 413 4 performance performance NOUN cana-844 413 5 assessment assessment NOUN cana-844 413 6 of of ADP cana-844 413 7 energy energy NOUN cana-844 413 8 efficient efficient ADJ cana-844 413 9 routing routing NOUN cana-844 413 10 protocol protocol NOUN cana-844 413 11 using use VERB cana-844 413 12 improved improved ADJ cana-844 413 13 leach leach NOUN cana-844 413 14 ” " PUNCT cana-844 413 15 , , PUNCT cana-844 413 16 international international ADJ cana-844 413 17 journal journal NOUN cana-844 413 18 of of ADP cana-844 413 19 wireless wireless ADJ cana-844 413 20 network network NOUN cana-844 413 21 security security NOUN cana-844 413 22 , , PUNCT cana-844 413 23 2021 2021 NUM cana-844 413 24 , , PUNCT cana-844 413 25 vol-7 vol-7 ADV cana-844 413 26 , , PUNCT cana-844 413 27 issue-1 issue-1 X cana-844 413 28 , , PUNCT cana-844 413 29 pp pp X cana-844 413 30 : : PUNCT cana-844 413 31 17 17 NUM cana-844 413 32 - - SYM cana-844 413 33 33 33 NUM cana-844 413 34 . . PUNCT