id sid tid token lemma pos cana-3976 1 1 communications communication NOUN cana-3976 1 2 on on ADP cana-3976 1 3 applied apply VERB cana-3976 1 4 nonlinear nonlinear ADJ cana-3976 1 5 analysis analysis NOUN cana-3976 1 6 issn issn NOUN cana-3976 1 7 : : PUNCT cana-3976 1 8 1074 1074 NUM cana-3976 1 9 - - PUNCT cana-3976 1 10 133x 133x NUM cana-3976 1 11 vol vol NOUN cana-3976 1 12 32 32 NUM cana-3976 1 13 no no NOUN cana-3976 1 14 . . PUNCT cana-3976 2 1 9s 9s NUM cana-3976 2 2 ( ( PUNCT cana-3976 2 3 2025 2025 NUM cana-3976 2 4 ) ) PUNCT cana-3976 2 5 702 702 NUM cana-3976 2 6 https://internationalpubls.com https://internationalpubls.com X cana-3976 2 7 a a DET cana-3976 2 8 novel novel ADJ cana-3976 2 9 & & CCONJ cana-3976 2 10 effective effective ADJ cana-3976 2 11 detection detection NOUN cana-3976 2 12 of of ADP cana-3976 2 13 alzheimer alzheimer PROPN cana-3976 2 14 's 's PART cana-3976 2 15 disease disease NOUN cana-3976 2 16 using use VERB cana-3976 2 17 extremely extremely ADV cana-3976 2 18 randomized randomized ADJ cana-3976 2 19 trees tree NOUN cana-3976 2 20 models model NOUN cana-3976 2 21 1mrs.bingimanorama 1mrs.bingimanorama PROPN cana-3976 2 22 devi devi NOUN cana-3976 2 23 , , PUNCT cana-3976 2 24 2dr 2dr NOUN cana-3976 2 25 . . PUNCT cana-3976 3 1 d. d. PROPN cana-3976 3 2 ganesh ganesh PROPN cana-3976 3 3 , , PUNCT cana-3976 3 4 1 1 NUM cana-3976 3 5 research research NOUN cana-3976 3 6 scholar scholar NOUN cana-3976 3 7 , , PUNCT cana-3976 3 8 department department NOUN cana-3976 3 9 of of ADP cana-3976 3 10 cse cse PROPN cana-3976 3 11 , , PUNCT cana-3976 3 12 mohan mohan PROPN cana-3976 3 13 babu babu PROPN cana-3976 3 14 university university PROPN cana-3976 3 15 ( ( PUNCT cana-3976 3 16 erstwhile erstwhile VERB cana-3976 3 17 sreevidyanikethan sreevidyanikethan ADP cana-3976 3 18 engineering engineering NOUN cana-3976 3 19 college college PROPN cana-3976 3 20 ( ( PUNCT cana-3976 3 21 autonomous autonomous ADJ cana-3976 3 22 ) ) PUNCT cana-3976 3 23 ) ) PUNCT cana-3976 3 24 , , PUNCT cana-3976 3 25 tirupati tirupati PROPN cana-3976 3 26 , , PUNCT cana-3976 3 27 andhra andhra PROPN cana-3976 3 28 pradesh pradesh PROPN cana-3976 3 29 , , PUNCT cana-3976 3 30 india india PROPN cana-3976 3 31 , , PUNCT cana-3976 3 32 bingimanorama@gmail.com bingimanorama@gmail.com PROPN cana-3976 3 33 2 2 NUM cana-3976 3 34 associate associate NOUN cana-3976 3 35 professor professor NOUN cana-3976 3 36 of of ADP cana-3976 3 37 cse cse PROPN cana-3976 3 38 , , PUNCT cana-3976 3 39 mohan mohan PROPN cana-3976 3 40 babu babu PROPN cana-3976 3 41 university university PROPN cana-3976 3 42 ( ( PUNCT cana-3976 3 43 erstwhile erstwhile VERB cana-3976 3 44 sreevidyanikethan sreevidyanikethan ADP cana-3976 3 45 engineering engineering NOUN cana-3976 3 46 college college PROPN cana-3976 3 47 ( ( PUNCT cana-3976 3 48 autonomous autonomous ADJ cana-3976 3 49 ) ) PUNCT cana-3976 3 50 ) ) PUNCT cana-3976 3 51 , , PUNCT cana-3976 3 52 tirupati tirupati PROPN cana-3976 3 53 , , PUNCT cana-3976 3 54 andhra andhra PROPN cana-3976 3 55 pradesh pradesh PROPN cana-3976 3 56 , , PUNCT cana-3976 3 57 india india PROPN cana-3976 3 58 , , PUNCT cana-3976 3 59 dgani05@gmail.com dgani05@gmail.com PROPN cana-3976 3 60 3 3 NUM cana-3976 3 61 article article NOUN cana-3976 3 62 history history NOUN cana-3976 3 63 : : PUNCT cana-3976 3 64 received receive VERB cana-3976 3 65 : : PUNCT cana-3976 3 66 10 10 NUM cana-3976 3 67 - - SYM cana-3976 3 68 11 11 NUM cana-3976 3 69 - - PUNCT cana-3976 3 70 2024 2024 NUM cana-3976 3 71 revised revise VERB cana-3976 3 72 : : PUNCT cana-3976 3 73 15 15 NUM cana-3976 3 74 - - SYM cana-3976 3 75 12 12 NUM cana-3976 3 76 - - PUNCT cana-3976 3 77 2024 2024 NUM cana-3976 3 78 accepted accept VERB cana-3976 3 79 : : PUNCT cana-3976 3 80 19 19 NUM cana-3976 3 81 - - PUNCT cana-3976 3 82 01 01 NUM cana-3976 3 83 - - PUNCT cana-3976 3 84 2025 2025 NUM cana-3976 3 85 abstract abstract NOUN cana-3976 3 86 : : PUNCT cana-3976 3 87 alzheimer alzheimer PROPN cana-3976 3 88 's 's PART cana-3976 3 89 disease disease NOUN cana-3976 3 90 ( ( PUNCT cana-3976 3 91 ad ad NOUN cana-3976 3 92 ) ) PUNCT cana-3976 3 93 is be AUX cana-3976 3 94 a a DET cana-3976 3 95 chronic chronic ADJ cana-3976 3 96 and and CCONJ cana-3976 3 97 irreversible irreversible ADJ cana-3976 3 98 brain brain NOUN cana-3976 3 99 disease disease NOUN cana-3976 3 100 without without ADP cana-3976 3 101 adequate adequate ADJ cana-3976 3 102 treatment treatment NOUN cana-3976 3 103 . . PUNCT cana-3976 4 1 however however ADV cana-3976 4 2 , , PUNCT cana-3976 4 3 currently currently ADV cana-3976 4 4 , , PUNCT cana-3976 4 5 available available ADJ cana-3976 4 6 drugs drug NOUN cana-3976 4 7 can can AUX cana-3976 4 8 slow slow VERB cana-3976 4 9 the the DET cana-3976 4 10 progression progression NOUN cana-3976 4 11 of of ADP cana-3976 4 12 the the DET cana-3976 4 13 condition condition NOUN cana-3976 4 14 . . PUNCT cana-3976 5 1 as as ADP cana-3976 5 2 a a DET cana-3976 5 3 result result NOUN cana-3976 5 4 , , PUNCT cana-3976 5 5 detecting detect VERB cana-3976 5 6 alzheimer alzheimer NOUN cana-3976 5 7 's 's PART cana-3976 5 8 disease disease NOUN cana-3976 5 9 early early ADV cana-3976 5 10 is be AUX cana-3976 5 11 essential essential ADJ cana-3976 5 12 to to ADP cana-3976 5 13 avoiding avoid VERB cana-3976 5 14 and and CCONJ cana-3976 5 15 limiting limit VERB cana-3976 5 16 the the DET cana-3976 5 17 disease disease NOUN cana-3976 5 18 's 's PART cana-3976 5 19 progression progression NOUN cana-3976 5 20 . . PUNCT cana-3976 6 1 the the DET cana-3976 6 2 primary primary ADJ cana-3976 6 3 purpose purpose NOUN cana-3976 6 4 of of ADP cana-3976 6 5 this this DET cana-3976 6 6 research research NOUN cana-3976 6 7 is be AUX cana-3976 6 8 to to PART cana-3976 6 9 establish establish VERB cana-3976 6 10 a a DET cana-3976 6 11 comprehensive comprehensive ADJ cana-3976 6 12 framework framework NOUN cana-3976 6 13 for for ADP cana-3976 6 14 the the DET cana-3976 6 15 early early ADJ cana-3976 6 16 identification identification NOUN cana-3976 6 17 of of ADP cana-3976 6 18 alzheimer alzheimer PROPN cana-3976 6 19 's 's PART cana-3976 6 20 disease disease NOUN cana-3976 6 21 and and CCONJ cana-3976 6 22 the the DET cana-3976 6 23 medical medical ADJ cana-3976 6 24 classification classification NOUN cana-3976 6 25 of of ADP cana-3976 6 26 the the DET cana-3976 6 27 disease disease NOUN cana-3976 6 28 's 's PART cana-3976 6 29 various various ADJ cana-3976 6 30 stages stage NOUN cana-3976 6 31 . . PUNCT cana-3976 7 1 alzheimer alzheimer PROPN cana-3976 7 2 's 's PART cana-3976 7 3 disease disease NOUN cana-3976 7 4 is be AUX cana-3976 7 5 classified classify VERB cana-3976 7 6 into into ADP cana-3976 7 7 two two NUM cana-3976 7 8 stages stage NOUN cana-3976 7 9 . . PUNCT cana-3976 8 1 the the DET cana-3976 8 2 proposed propose VERB cana-3976 8 3 work work NOUN cana-3976 8 4 employed employ VERB cana-3976 8 5 multiple multiple ADJ cana-3976 8 6 machine machine NOUN cana-3976 8 7 learning learning NOUN cana-3976 8 8 ( ( PUNCT cana-3976 8 9 ml ml NOUN cana-3976 8 10 ) ) PUNCT cana-3976 8 11 approaches approach NOUN cana-3976 8 12 such such ADJ cana-3976 8 13 as as ADP cana-3976 8 14 gradient gradient ADJ cana-3976 8 15 boost boost NOUN cana-3976 8 16 ( ( PUNCT cana-3976 8 17 gb gb NOUN cana-3976 8 18 ) ) PUNCT cana-3976 8 19 , , PUNCT cana-3976 8 20 decision decision NOUN cana-3976 8 21 tree tree NOUN cana-3976 8 22 ( ( PUNCT cana-3976 8 23 dt dt PROPN cana-3976 8 24 ) ) PUNCT cana-3976 8 25 , , PUNCT cana-3976 8 26 support support NOUN cana-3976 8 27 vector vector NOUN cana-3976 8 28 machine machine NOUN cana-3976 8 29 ( ( PUNCT cana-3976 8 30 svm svm PROPN cana-3976 8 31 ) ) PUNCT cana-3976 8 32 , , PUNCT cana-3976 8 33 and and CCONJ cana-3976 8 34 extra extra ADJ cana-3976 8 35 tree tree NOUN cana-3976 8 36 algorithm algorithm NOUN cana-3976 8 37 ( ( PUNCT cana-3976 8 38 eta eta NOUN cana-3976 8 39 ) ) PUNCT cana-3976 8 40 to to PART cana-3976 8 41 diagnose diagnose VERB cana-3976 8 42 and and CCONJ cana-3976 8 43 classify classify VERB cana-3976 8 44 alzheimer alzheimer PROPN cana-3976 8 45 's 's PART cana-3976 8 46 disease disease NOUN cana-3976 8 47 earlier early ADV cana-3976 8 48 using use VERB cana-3976 8 49 the the DET cana-3976 8 50 open open ADJ cana-3976 8 51 access access NOUN cana-3976 8 52 series series NOUN cana-3976 8 53 of of ADP cana-3976 8 54 imaging imaging NOUN cana-3976 8 55 studies study NOUN cana-3976 8 56 ( ( PUNCT cana-3976 8 57 oasis oasis NOUN cana-3976 8 58 ) ) PUNCT cana-3976 8 59 dataset dataset NOUN cana-3976 8 60 , , PUNCT cana-3976 8 61 with with ADP cana-3976 8 62 the the DET cana-3976 8 63 eta eta PROPN cana-3976 8 64 classifier classifier NOUN cana-3976 8 65 achieving achieve VERB cana-3976 8 66 significant significant ADJ cana-3976 8 67 performance performance NOUN cana-3976 8 68 and and CCONJ cana-3976 8 69 result result NOUN cana-3976 8 70 . . PUNCT cana-3976 9 1 the the DET cana-3976 9 2 eta eta PROPN cana-3976 9 3 classifier classifier NOUN cana-3976 9 4 , , PUNCT cana-3976 9 5 in in ADP cana-3976 9 6 particular particular ADJ cana-3976 9 7 , , PUNCT cana-3976 9 8 outperformed outperform VERB cana-3976 9 9 the the DET cana-3976 9 10 others other NOUN cana-3976 9 11 regarding regard VERB cana-3976 9 12 total total ADJ cana-3976 9 13 classification classification NOUN cana-3976 9 14 performance performance NOUN cana-3976 9 15 . . PUNCT cana-3976 10 1 the the DET cana-3976 10 2 proposed propose VERB cana-3976 10 3 eta eta PROPN cana-3976 10 4 achieves achieve VERB cana-3976 10 5 an an DET cana-3976 10 6 accuracy accuracy NOUN cana-3976 10 7 of of ADP cana-3976 10 8 0.88 0.88 NUM cana-3976 10 9 , , PUNCT cana-3976 10 10 precision precision NOUN cana-3976 10 11 of of ADP cana-3976 10 12 0.93 0.93 NUM cana-3976 10 13 , , PUNCT cana-3976 10 14 recall recall NOUN cana-3976 10 15 of of ADP cana-3976 10 16 0.85 0.85 NUM cana-3976 10 17 , , PUNCT cana-3976 10 18 and and CCONJ cana-3976 10 19 f1 f1 NOUN cana-3976 10 20 - - PUNCT cana-3976 10 21 score score NOUN cana-3976 10 22 of of ADP cana-3976 10 23 0.89 0.89 NUM cana-3976 10 24 . . PUNCT cana-3976 11 1 the the DET cana-3976 11 2 machine machine NOUN cana-3976 11 3 learning learning NOUN cana-3976 11 4 ( ( PUNCT cana-3976 11 5 ml ml NOUN cana-3976 11 6 ) ) PUNCT cana-3976 11 7 technique technique NOUN cana-3976 11 8 that that PRON cana-3976 11 9 we we PRON cana-3976 11 10 have have AUX cana-3976 11 11 selected select VERB cana-3976 11 12 to to PART cana-3976 11 13 apply apply VERB cana-3976 11 14 for for ADP cana-3976 11 15 alzheimer alzheimer PROPN cana-3976 11 16 's 's PART cana-3976 11 17 disease disease NOUN cana-3976 11 18 detection detection NOUN cana-3976 11 19 is be AUX cana-3976 11 20 the the DET cana-3976 11 21 extremely extremely ADV cana-3976 11 22 randomised randomised ADJ cana-3976 11 23 trees tree NOUN cana-3976 11 24 ( ( PUNCT cana-3976 11 25 extra extra ADJ cana-3976 11 26 trees tree NOUN cana-3976 11 27 ) ) PUNCT cana-3976 11 28 algorithm algorithm NOUN cana-3976 11 29 . . PUNCT cana-3976 12 1 this this PRON cana-3976 12 2 was be AUX cana-3976 12 3 a a DET cana-3976 12 4 conscious conscious ADJ cana-3976 12 5 decision decision NOUN cana-3976 12 6 on on ADP cana-3976 12 7 our our PRON cana-3976 12 8 side side NOUN cana-3976 12 9 . . PUNCT cana-3976 13 1 we we PRON cana-3976 13 2 may may AUX cana-3976 13 3 classify classify VERB cana-3976 13 4 ad ad NOUN cana-3976 13 5 with with ADP cana-3976 13 6 high high ADJ cana-3976 13 7 accuracy accuracy NOUN cana-3976 13 8 using use VERB cana-3976 13 9 machine machine NOUN cana-3976 13 10 learning learning NOUN cana-3976 13 11 methods method NOUN cana-3976 13 12 . . PUNCT cana-3976 14 1 keywords keyword NOUN cana-3976 14 2 : : PUNCT cana-3976 14 3 alzheimer alzheimer PROPN cana-3976 14 4 โ€™s โ€™s PART cana-3976 14 5 disease disease NOUN cana-3976 14 6 ; ; PUNCT cana-3976 14 7 gradient gradient ADJ cana-3976 14 8 boosting boosting NOUN cana-3976 14 9 , , PUNCT cana-3976 14 10 machine machine NOUN cana-3976 14 11 learning learning NOUN cana-3976 14 12 ; ; PUNCT cana-3976 14 13 dementia dementia NOUN cana-3976 14 14 , , PUNCT cana-3976 14 15 extra extra ADJ cana-3976 14 16 tree tree NOUN cana-3976 14 17 1 1 NUM cana-3976 14 18 . . PUNCT cana-3976 14 19 introduction introduction NOUN cana-3976 14 20 in in ADP cana-3976 14 21 the the DET cana-3976 14 22 current current ADJ cana-3976 14 23 era era NOUN cana-3976 14 24 , , PUNCT cana-3976 14 25 dementia dementia NOUN cana-3976 14 26 is be AUX cana-3976 14 27 no no ADV cana-3976 14 28 longer long ADV cana-3976 14 29 considered consider VERB cana-3976 14 30 a a DET cana-3976 14 31 unique unique ADJ cana-3976 14 32 disease disease NOUN cana-3976 14 33 . . PUNCT cana-3976 15 1 it it PRON cana-3976 15 2 is be AUX cana-3976 15 3 a a DET cana-3976 15 4 broad broad ADJ cana-3976 15 5 term term NOUN cana-3976 15 6 for for ADP cana-3976 15 7 symptoms symptom NOUN cana-3976 15 8 caused cause VERB cana-3976 15 9 by by ADP cana-3976 15 10 a a DET cana-3976 15 11 decline decline NOUN cana-3976 15 12 in in ADP cana-3976 15 13 memory memory NOUN cana-3976 15 14 or or CCONJ cana-3976 15 15 other other ADJ cana-3976 15 16 thinking thinking NOUN cana-3976 15 17 skills skill NOUN cana-3976 15 18 severe severe ADJ cana-3976 15 19 enough enough ADV cana-3976 15 20 to to PART cana-3976 15 21 impair impair VERB cana-3976 15 22 a a DET cana-3976 15 23 person person NOUN cana-3976 15 24 's 's PART cana-3976 15 25 ability ability NOUN cana-3976 15 26 to to PART cana-3976 15 27 do do AUX cana-3976 15 28 daily daily ADJ cana-3976 15 29 tasks task NOUN cana-3976 15 30 . . PUNCT cana-3976 16 1 alzheimer alzheimer PROPN cana-3976 16 2 's 's PART cana-3976 16 3 disease disease NOUN cana-3976 16 4 or or CCONJ cana-3976 16 5 another another DET cana-3976 16 6 type type NOUN cana-3976 16 7 of of ADP cana-3976 16 8 dementia dementia NOUN cana-3976 16 9 can can AUX cana-3976 16 10 induce induce VERB cana-3976 16 11 these these DET cana-3976 16 12 symptoms symptom NOUN cana-3976 16 13 . . PUNCT cana-3976 17 1 alzheimer alzheimer PROPN cana-3976 17 2 's 's PART cana-3976 17 3 disease disease NOUN cana-3976 17 4 is be AUX cana-3976 17 5 responsible responsible ADJ cana-3976 17 6 for for ADP cana-3976 17 7 most most ADJ cana-3976 17 8 cases case NOUN cana-3976 17 9 ( ( PUNCT cana-3976 17 10 60 60 NUM cana-3976 17 11 - - SYM cana-3976 17 12 80 80 NUM cana-3976 17 13 % % NOUN cana-3976 17 14 ) ) PUNCT cana-3976 17 15 . . PUNCT cana-3976 18 1 vascular vascular ADJ cana-3976 18 2 dementia dementia NOUN cana-3976 18 3 is be AUX cana-3976 18 4 the the DET cana-3976 18 5 second second ADJ cana-3976 18 6 most most ADV cana-3976 18 7 common common ADJ cana-3976 18 8 type type NOUN cana-3976 18 9 of of ADP cana-3976 18 10 dementia dementia NOUN cana-3976 18 11 after after ADP cana-3976 18 12 alzheimer alzheimer PROPN cana-3976 18 13 's 's PART cana-3976 18 14 disease disease NOUN cana-3976 18 15 , , PUNCT cana-3976 18 16 which which PRON cana-3976 18 17 is be AUX cana-3976 18 18 the the DET cana-3976 18 19 primary primary ADJ cana-3976 18 20 cause cause NOUN cana-3976 18 21 of of ADP cana-3976 18 22 dementia dementia NOUN cana-3976 18 23 . . PUNCT cana-3976 19 1 however however ADV cana-3976 19 2 , , PUNCT cana-3976 19 3 dementia dementia NOUN cana-3976 19 4 symptoms symptom NOUN cana-3976 19 5 can can AUX cana-3976 19 6 also also ADV cana-3976 19 7 be be AUX cana-3976 19 8 caused cause VERB cana-3976 19 9 by by ADP cana-3976 19 10 several several ADJ cana-3976 19 11 other other ADJ cana-3976 19 12 disorders disorder NOUN cana-3976 19 13 , , PUNCT cana-3976 19 14 some some PRON cana-3976 19 15 of of ADP cana-3976 19 16 which which PRON cana-3976 19 17 are be AUX cana-3976 19 18 treatable treatable ADJ cana-3976 19 19 and and CCONJ cana-3976 19 20 reversible reversible ADJ cana-3976 19 21 , , PUNCT cana-3976 19 22 such such ADJ cana-3976 19 23 as as ADP cana-3976 19 24 thyroid thyroid NOUN cana-3976 19 25 problems problem NOUN cana-3976 19 26 or or CCONJ cana-3976 19 27 vitamin vitamin NOUN cana-3976 19 28 deficiencies deficiency NOUN cana-3976 19 29 . . PUNCT cana-3976 20 1 alzheimer alzheimer PROPN cana-3976 20 2 's 's PART cana-3976 20 3 disease disease NOUN cana-3976 20 4 ( ( PUNCT cana-3976 20 5 ad ad NOUN cana-3976 20 6 ) ) PUNCT cana-3976 20 7 is be AUX cana-3976 20 8 a a DET cana-3976 20 9 type type NOUN cana-3976 20 10 of of ADP cana-3976 20 11 dementia dementia NOUN cana-3976 20 12 having have VERB cana-3976 20 13 no no DET cana-3976 20 14 specific specific ADJ cana-3976 20 15 medication medication NOUN cana-3976 20 16 and and CCONJ cana-3976 20 17 ranks rank VERB cana-3976 20 18 sixth sixth ADJ cana-3976 20 19 primary primary ADJ cana-3976 20 20 death death NOUN cana-3976 20 21 cause cause NOUN cana-3976 20 22 in in ADP cana-3976 20 23 the the DET cana-3976 20 24 united united PROPN cana-3976 20 25 states states PROPN cana-3976 20 26 of of ADP cana-3976 20 27 america america PROPN cana-3976 21 1 [ [ X cana-3976 21 2 1 1 NUM cana-3976 21 3 , , PUNCT cana-3976 21 4 2 2 NUM cana-3976 21 5 ] ] PUNCT cana-3976 21 6 . . PUNCT cana-3976 22 1 gradual gradual ADJ cana-3976 22 2 atrophy atrophy NOUN cana-3976 22 3 of of ADP cana-3976 22 4 the the DET cana-3976 22 5 cerebral cerebral ADJ cana-3976 22 6 cortex cortex NOUN cana-3976 22 7 characterizes characterize VERB cana-3976 22 8 this this PRON cana-3976 22 9 , , PUNCT cana-3976 22 10 developing develop VERB cana-3976 22 11 communications communication NOUN cana-3976 22 12 on on ADP cana-3976 22 13 applied apply VERB cana-3976 22 14 nonlinear nonlinear ADJ cana-3976 22 15 analysis analysis NOUN cana-3976 22 16 issn issn NOUN cana-3976 22 17 : : PUNCT cana-3976 22 18 1074 1074 NUM cana-3976 22 19 - - PUNCT cana-3976 22 20 133x 133x NUM cana-3976 22 21 vol vol NOUN cana-3976 22 22 32 32 NUM cana-3976 22 23 no no NOUN cana-3976 22 24 . . PUNCT cana-3976 23 1 9s 9s NUM cana-3976 23 2 ( ( PUNCT cana-3976 23 3 2025 2025 NUM cana-3976 23 4 ) ) PUNCT cana-3976 24 1 703 703 NUM cana-3976 24 2 https://internationalpubls.com https://internationalpubls.com X cana-3976 24 3 cognitive cognitive ADJ cana-3976 24 4 difficulties difficulty NOUN cana-3976 24 5 and and CCONJ cana-3976 24 6 memory memory NOUN cana-3976 24 7 loss loss NOUN cana-3976 24 8 [ [ X cana-3976 24 9 3 3 NUM cana-3976 24 10 ] ] PUNCT cana-3976 24 11 . . PUNCT cana-3976 25 1 new new ADJ cana-3976 25 2 technology technology NOUN cana-3976 25 3 has have AUX cana-3976 25 4 enabled enable VERB cana-3976 25 5 the the DET cana-3976 25 6 use use NOUN cana-3976 25 7 of of ADP cana-3976 25 8 computer computer NOUN cana-3976 25 9 - - PUNCT cana-3976 25 10 assisted assist VERB cana-3976 25 11 algorithms algorithm NOUN cana-3976 25 12 in in ADP cana-3976 25 13 hospitals hospital NOUN cana-3976 25 14 , , PUNCT cana-3976 25 15 potentially potentially ADV cana-3976 25 16 increasing increase VERB cana-3976 25 17 the the DET cana-3976 25 18 accuracy accuracy NOUN cana-3976 25 19 and and CCONJ cana-3976 25 20 speed speed NOUN cana-3976 25 21 of of ADP cana-3976 25 22 diagnosis diagnosis NOUN cana-3976 25 23 . . PUNCT cana-3976 26 1 because because SCONJ cana-3976 26 2 of of ADP cana-3976 26 3 recent recent ADJ cana-3976 26 4 developments development NOUN cana-3976 26 5 in in ADP cana-3976 26 6 the the DET cana-3976 26 7 healthcare healthcare NOUN cana-3976 26 8 sector sector NOUN cana-3976 26 9 , , PUNCT cana-3976 26 10 which which PRON cana-3976 26 11 have have AUX cana-3976 26 12 produced produce VERB cana-3976 26 13 powerful powerful ADJ cana-3976 26 14 tools tool NOUN cana-3976 26 15 for for ADP cana-3976 26 16 collecting collect VERB cana-3976 26 17 and and CCONJ cana-3976 26 18 retrieving retrieve VERB cana-3976 26 19 usable usable ADJ cana-3976 26 20 neuroimaging neuroimaging NOUN cana-3976 26 21 data datum NOUN cana-3976 26 22 to to PART cana-3976 26 23 monitor monitor VERB cana-3976 26 24 neurodegeneration neurodegeneration NOUN cana-3976 26 25 , , PUNCT cana-3976 26 26 there there PRON cana-3976 26 27 is be VERB cana-3976 26 28 a a DET cana-3976 26 29 lot lot NOUN cana-3976 26 30 of of ADP cana-3976 26 31 excitement excitement NOUN cana-3976 26 32 about about ADP cana-3976 26 33 using use VERB cana-3976 26 34 pictures picture NOUN cana-3976 26 35 for for ADP cana-3976 26 36 diagnosis diagnosis NOUN cana-3976 26 37 and and CCONJ cana-3976 26 38 prognosis prognosis NOUN cana-3976 26 39 . . PUNCT cana-3976 27 1 one one NUM cana-3976 27 2 area area NOUN cana-3976 27 3 where where SCONJ cana-3976 27 4 computer computer NOUN cana-3976 27 5 algorithms algorithm NOUN cana-3976 27 6 may may AUX cana-3976 27 7 produce produce VERB cana-3976 27 8 more more ADV cana-3976 27 9 accurate accurate ADJ cana-3976 27 10 findings finding NOUN cana-3976 27 11 than than ADP cana-3976 27 12 medical medical ADJ cana-3976 27 13 practitioners practitioner NOUN cana-3976 27 14 ( ( PUNCT cana-3976 27 15 for for ADP cana-3976 27 16 example example NOUN cana-3976 27 17 , , PUNCT cana-3976 27 18 radiologists radiologist NOUN cana-3976 27 19 ) ) PUNCT cana-3976 27 20 is be AUX cana-3976 27 21 ad ad NOUN cana-3976 27 22 detection detection NOUN cana-3976 27 23 . . PUNCT cana-3976 28 1 this this DET cana-3976 28 2 ailment ailment NOUN cana-3976 28 3 first first ADV cana-3976 28 4 touches touch VERB cana-3976 28 5 memory memory NOUN cana-3976 28 6 function function NOUN cana-3976 28 7 , , PUNCT cana-3976 28 8 then then ADV cana-3976 28 9 gradually gradually ADV cana-3976 28 10 limits limit VERB cana-3976 28 11 all all DET cana-3976 28 12 cognitive cognitive ADJ cana-3976 28 13 tasks task NOUN cana-3976 28 14 , , PUNCT cana-3976 28 15 eventually eventually ADV cana-3976 28 16 leading lead VERB cana-3976 28 17 to to ADP cana-3976 28 18 death death NOUN cana-3976 28 19 . . PUNCT cana-3976 29 1 patients patient NOUN cana-3976 29 2 with with ADP cana-3976 29 3 alzheimer alzheimer PROPN cana-3976 29 4 's 's PART cana-3976 29 5 disease disease NOUN cana-3976 29 6 risk risk NOUN cana-3976 29 7 becoming becoming AUX cana-3976 29 8 disoriented disorient VERB cana-3976 29 9 and and CCONJ cana-3976 29 10 forgetting forget VERB cana-3976 29 11 how how SCONJ cana-3976 29 12 to to PART cana-3976 29 13 do do VERB cana-3976 29 14 ordinary ordinary ADJ cana-3976 29 15 tasks task NOUN cana-3976 29 16 . . PUNCT cana-3976 30 1 they they PRON cana-3976 30 2 can can AUX cana-3976 30 3 even even ADV cana-3976 30 4 fail fail VERB cana-3976 30 5 to to PART cana-3976 30 6 recognize recognize VERB cana-3976 30 7 their their PRON cana-3976 30 8 own own ADJ cana-3976 30 9 family family NOUN cana-3976 30 10 . . PUNCT cana-3976 31 1 alzheimer alzheimer PROPN cana-3976 31 2 's 's PART cana-3976 31 3 disease disease NOUN cana-3976 31 4 and and CCONJ cana-3976 31 5 its its PRON cana-3976 31 6 many many ADJ cana-3976 31 7 stages stage NOUN cana-3976 31 8 are be AUX cana-3976 31 9 difficult difficult ADJ cana-3976 31 10 to to PART cana-3976 31 11 diagnose diagnose VERB cana-3976 31 12 since since SCONJ cana-3976 31 13 symptoms symptom NOUN cana-3976 31 14 of of ADP cana-3976 31 15 the the DET cana-3976 31 16 disease disease NOUN cana-3976 31 17 can can AUX cana-3976 31 18 be be AUX cana-3976 31 19 found find VERB cana-3976 31 20 in in ADP cana-3976 31 21 the the DET cana-3976 31 22 brains brain NOUN cana-3976 31 23 of of ADP cana-3976 31 24 old old ADJ cana-3976 31 25 persons person NOUN cana-3976 31 26 who who PRON cana-3976 31 27 do do AUX cana-3976 31 28 not not PART cana-3976 31 29 have have VERB cana-3976 31 30 the the DET cana-3976 31 31 disease disease NOUN cana-3976 31 32 . . PUNCT cana-3976 32 1 alzheimer alzheimer PROPN cana-3976 32 2 's 's PART cana-3976 32 3 disease disease NOUN cana-3976 32 4 is be AUX cana-3976 32 5 diagnosed diagnose VERB cana-3976 32 6 in in ADP cana-3976 32 7 medical medical ADJ cana-3976 32 8 practice practice NOUN cana-3976 32 9 utilizing utilize VERB cana-3976 32 10 information information NOUN cana-3976 32 11 obtained obtain VERB cana-3976 32 12 from from ADP cana-3976 32 13 a a DET cana-3976 32 14 lengthy lengthy ADJ cana-3976 32 15 conversation conversation NOUN cana-3976 32 16 with with ADP cana-3976 32 17 a a DET cana-3976 32 18 patient patient NOUN cana-3976 32 19 's 's PART cana-3976 32 20 family family NOUN cana-3976 32 21 members member NOUN cana-3976 32 22 who who PRON cana-3976 32 23 have have VERB cana-3976 32 24 the the DET cana-3976 32 25 disease disease NOUN cana-3976 32 26 . . PUNCT cana-3976 33 1 in in ADP cana-3976 33 2 2018 2018 NUM cana-3976 33 3 , , PUNCT cana-3976 33 4 they they PRON cana-3976 33 5 expected expect VERB cana-3976 33 6 dementia dementia NOUN cana-3976 33 7 to to PART cana-3976 33 8 affect affect VERB cana-3976 33 9 35.6 35.6 NUM cana-3976 33 10 million million NUM cana-3976 33 11 individuals individual NOUN cana-3976 33 12 over over ADP cana-3976 33 13 60 60 NUM cana-3976 33 14 worldwide worldwide ADV cana-3976 33 15 , , PUNCT cana-3976 33 16 including include VERB cana-3976 33 17 310,000 310,000 NUM cana-3976 33 18 in in ADP cana-3976 33 19 australia australia PROPN cana-3976 33 20 . . PUNCT cana-3976 34 1 2050 2050 NUM cana-3976 34 2 expect expect VERB cana-3976 34 3 this this DET cana-3976 34 4 amount amount NOUN cana-3976 34 5 to to ADP cana-3976 34 6 ( ( PUNCT cana-3976 34 7 almost almost ADV cana-3976 34 8 ) ) PUNCT cana-3976 34 9 triple triple ADJ cana-3976 34 10 , , PUNCT cana-3976 34 11 bringing bring VERB cana-3976 34 12 the the DET cana-3976 34 13 total total ADJ cana-3976 34 14 number number NOUN cana-3976 34 15 of of ADP cana-3976 34 16 people people NOUN cana-3976 34 17 in in ADP cana-3976 34 18 the the DET cana-3976 34 19 world world NOUN cana-3976 34 20 to to ADP cana-3976 34 21 201 201 NUM cana-3976 34 22 million million NUM cana-3976 34 23 . . PUNCT cana-3976 35 1 in in ADP cana-3976 35 2 2018 2018 NUM cana-3976 35 3 , , PUNCT cana-3976 35 4 dementia dementia NOUN cana-3976 35 5 killed kill VERB cana-3976 35 6 9586 9586 NUM cana-3976 35 7 people people NOUN cana-3976 35 8 , , PUNCT cana-3976 35 9 making make VERB cana-3976 35 10 it it PRON cana-3976 35 11 the the DET cana-3976 35 12 country country NOUN cana-3976 35 13 's 's PART cana-3976 35 14 second second ADV cana-3976 35 15 - - PUNCT cana-3976 35 16 biggest big ADJ cana-3976 35 17 cause cause NOUN cana-3976 35 18 of of ADP cana-3976 35 19 death death NOUN cana-3976 35 20 [ [ X cana-3976 35 21 4 4 NUM cana-3976 35 22 ] ] PUNCT cana-3976 35 23 . . PUNCT cana-3976 36 1 alzheimer alzheimer PROPN cana-3976 36 2 's 's PART cana-3976 36 3 disease disease NOUN cana-3976 36 4 ( ( PUNCT cana-3976 36 5 ad ad NOUN cana-3976 36 6 ) ) PUNCT cana-3976 36 7 accounts account NOUN cana-3976 36 8 for for ADP cana-3976 36 9 60 60 NUM cana-3976 36 10 % % NOUN cana-3976 36 11 to to PART cana-3976 36 12 80 80 NUM cana-3976 36 13 % % NOUN cana-3976 36 14 of of ADP cana-3976 36 15 all all DET cana-3976 36 16 dementia dementia NOUN cana-3976 36 17 cases case NOUN cana-3976 36 18 [ [ X cana-3976 36 19 5 5 NUM cana-3976 36 20 , , PUNCT cana-3976 36 21 6 6 NUM cana-3976 36 22 ] ] PUNCT cana-3976 36 23 . . PUNCT cana-3976 37 1 even even ADV cana-3976 37 2 though though SCONJ cana-3976 37 3 several several ADJ cana-3976 37 4 therapeutic therapeutic ADJ cana-3976 37 5 options option NOUN cana-3976 37 6 have have AUX cana-3976 37 7 been be AUX cana-3976 37 8 examined examine VERB cana-3976 37 9 to to PART cana-3976 37 10 reduce reduce VERB cana-3976 37 11 or or CCONJ cana-3976 37 12 stop stop VERB cana-3976 37 13 the the DET cana-3976 37 14 progression progression NOUN cana-3976 37 15 of of ADP cana-3976 37 16 the the DET cana-3976 37 17 disease disease NOUN cana-3976 37 18 [ [ X cana-3976 37 19 7 7 NUM cana-3976 37 20 ] ] PUNCT cana-3976 37 21 , , PUNCT cana-3976 37 22 very very ADV cana-3976 37 23 little little ADJ cana-3976 37 24 evidence evidence NOUN cana-3976 37 25 of of ADP cana-3976 37 26 efficacy efficacy NOUN cana-3976 37 27 has have AUX cana-3976 37 28 been be AUX cana-3976 37 29 found.people found.people NUM cana-3976 37 30 diagnosed diagnose VERB cana-3976 37 31 early early ADV cana-3976 37 32 are be AUX cana-3976 37 33 more more ADV cana-3976 37 34 likely likely ADJ cana-3976 37 35 to to PART cana-3976 37 36 benefit benefit VERB cana-3976 37 37 from from ADP cana-3976 37 38 supportive supportive ADJ cana-3976 37 39 therapy therapy NOUN cana-3976 37 40 , , PUNCT cana-3976 37 41 which which PRON cana-3976 37 42 allows allow VERB cana-3976 37 43 them they PRON cana-3976 37 44 to to PART cana-3976 37 45 spend spend VERB cana-3976 37 46 more more ADJ cana-3976 37 47 time time NOUN cana-3976 37 48 at at ADP cana-3976 37 49 home home NOUN cana-3976 37 50 and and CCONJ cana-3976 37 51 reduces reduce VERB cana-3976 37 52 their their PRON cana-3976 37 53 chances chance NOUN cana-3976 37 54 of of ADP cana-3976 37 55 being be AUX cana-3976 37 56 hospitalized hospitalize VERB cana-3976 37 57 [ [ X cana-3976 37 58 8 8 NUM cana-3976 37 59 , , PUNCT cana-3976 37 60 9 9 NUM cana-3976 37 61 ] ] PUNCT cana-3976 37 62 . . PUNCT cana-3976 38 1 job job NOUN cana-3976 38 2 - - PUNCT cana-3976 38 3 specific specific ADJ cana-3976 38 4 properties property NOUN cana-3976 38 5 [ [ X cana-3976 38 6 10 10 NUM cana-3976 38 7 , , PUNCT cana-3976 38 8 11 11 NUM cana-3976 38 9 ] ] PUNCT cana-3976 38 10 are be AUX cana-3976 38 11 extracted extract VERB cana-3976 38 12 from from ADP cana-3976 38 13 images image NOUN cana-3976 38 14 to to PART cana-3976 38 15 train train VERB cana-3976 38 16 supervised supervised ADJ cana-3976 38 17 models model NOUN cana-3976 38 18 [ [ X cana-3976 38 19 12 12 NUM cana-3976 38 20 ] ] PUNCT cana-3976 38 21 . . PUNCT cana-3976 39 1 they they PRON cana-3976 39 2 need need VERB cana-3976 39 3 human human ADJ cana-3976 39 4 workers worker NOUN cana-3976 39 5 to to PART cana-3976 39 6 extract extract VERB cana-3976 39 7 these these DET cana-3976 39 8 features feature NOUN cana-3976 39 9 , , PUNCT cana-3976 39 10 which which PRON cana-3976 39 11 typically typically ADV cana-3976 39 12 require require VERB cana-3976 39 13 much much ADJ cana-3976 39 14 work work NOUN cana-3976 39 15 , , PUNCT cana-3976 39 16 time time NOUN cana-3976 39 17 , , PUNCT cana-3976 39 18 and and CCONJ cana-3976 39 19 financial financial ADJ cana-3976 39 20 investment investment NOUN cana-3976 39 21 . . PUNCT cana-3976 40 1 as as ADP cana-3976 40 2 a a DET cana-3976 40 3 result result NOUN cana-3976 40 4 , , PUNCT cana-3976 40 5 it it PRON cana-3976 40 6 is be AUX cana-3976 40 7 the the DET cana-3976 40 8 most most ADV cana-3976 40 9 challenging challenging ADJ cana-3976 40 10 problem problem NOUN cana-3976 40 11 for for SCONJ cana-3976 40 12 data datum NOUN cana-3976 40 13 scientists scientist NOUN cana-3976 40 14 to to PART cana-3976 40 15 overcome overcome VERB cana-3976 40 16 . . PUNCT cana-3976 41 1 on on ADP cana-3976 41 2 the the DET cana-3976 41 3 other other ADJ cana-3976 41 4 hand hand NOUN cana-3976 41 5 , , PUNCT cana-3976 41 6 deep deep ADJ cana-3976 41 7 learning learning NOUN cana-3976 41 8 algorithms algorithm NOUN cana-3976 41 9 have have AUX cana-3976 41 10 advanced advance VERB cana-3976 41 11 to to ADP cana-3976 41 12 the the DET cana-3976 41 13 point point NOUN cana-3976 41 14 where where SCONJ cana-3976 41 15 they they PRON cana-3976 41 16 can can AUX cana-3976 41 17 now now ADV cana-3976 41 18 extract extract VERB cana-3976 41 19 features feature NOUN cana-3976 41 20 from from ADP cana-3976 41 21 visual visual ADJ cana-3976 41 22 data datum NOUN cana-3976 41 23 without without ADP cana-3976 41 24 human human ADJ cana-3976 41 25 interaction interaction NOUN cana-3976 41 26 . . PUNCT cana-3976 42 1 the the DET cana-3976 42 2 purpose purpose NOUN cana-3976 42 3 of of ADP cana-3976 42 4 this this DET cana-3976 42 5 paper paper NOUN cana-3976 42 6 is be AUX cana-3976 42 7 to to PART cana-3976 42 8 develop develop VERB cana-3976 42 9 an an DET cana-3976 42 10 automated automate VERB cana-3976 42 11 model model NOUN cana-3976 42 12 for for ADP cana-3976 42 13 alzheimer alzheimer PROPN cana-3976 42 14 's 's PART cana-3976 42 15 disease disease NOUN cana-3976 42 16 patients patient NOUN cana-3976 42 17 using use VERB cana-3976 42 18 machine machine NOUN cana-3976 42 19 learning learning NOUN cana-3976 42 20 ( ( PUNCT cana-3976 42 21 ml ml NOUN cana-3976 42 22 ) ) PUNCT cana-3976 42 23 approaches approach NOUN cana-3976 42 24 like like ADP cana-3976 42 25 dt dt PROPN cana-3976 42 26 , , PUNCT cana-3976 42 27 gb gb PROPN cana-3976 42 28 , , PUNCT cana-3976 42 29 eta eta PROPN cana-3976 42 30 , , PUNCT cana-3976 42 31 and and CCONJ cana-3976 42 32 svm svm PROPN cana-3976 42 33 , , PUNCT cana-3976 42 34 the the DET cana-3976 42 35 classification classification NOUN cana-3976 42 36 is be AUX cana-3976 42 37 based base VERB cana-3976 42 38 on on ADP cana-3976 42 39 mri mri NOUN cana-3976 42 40 patient patient NOUN cana-3976 42 41 images image NOUN cana-3976 42 42 of of ADP cana-3976 42 43 the the DET cana-3976 42 44 oasis oasis NOUN cana-3976 42 45 repository repository NOUN cana-3976 42 46 . . PUNCT cana-3976 43 1 also also ADV cana-3976 43 2 , , PUNCT cana-3976 43 3 the the DET cana-3976 43 4 proposed propose VERB cana-3976 43 5 classifier classifier NOUN cana-3976 43 6 reaches reach VERB cana-3976 43 7 88.21 88.21 NUM cana-3976 43 8 % % NOUN cana-3976 43 9 accuracy accuracy NOUN cana-3976 43 10 , , PUNCT cana-3976 43 11 as as SCONJ cana-3976 43 12 related relate VERB cana-3976 43 13 to to ADP cana-3976 43 14 the the DET cana-3976 43 15 other other ADJ cana-3976 43 16 works work NOUN cana-3976 43 17 stated state VERB cana-3976 43 18 in in ADP cana-3976 43 19 the the DET cana-3976 43 20 literature literature NOUN cana-3976 43 21 . . PUNCT cana-3976 44 1 there there PRON cana-3976 44 2 are be VERB cana-3976 44 3 no no DET cana-3976 44 4 easily easily ADV cana-3976 44 5 accessible accessible ADJ cana-3976 44 6 articles article NOUN cana-3976 44 7 that that PRON cana-3976 44 8 employ employ VERB cana-3976 44 9 eta eta INTJ cana-3976 44 10 to to PART cana-3976 44 11 detect detect VERB cana-3976 44 12 mri mri NOUN cana-3976 44 13 - - PUNCT cana-3976 44 14 associated associate VERB cana-3976 44 15 alzheimer alzheimer NOUN cana-3976 44 16 's 's PART cana-3976 44 17 disease disease NOUN cana-3976 44 18 ( ( PUNCT cana-3976 44 19 ad ad NOUN cana-3976 44 20 ) ) PUNCT cana-3976 44 21 . . PUNCT cana-3976 45 1 2 2 X cana-3976 45 2 . . X cana-3976 45 3 related relate VERB cana-3976 45 4 work work NOUN cana-3976 45 5 in in ADP cana-3976 45 6 this this DET cana-3976 45 7 section section NOUN cana-3976 45 8 , , PUNCT cana-3976 45 9 ad ad NOUN cana-3976 45 10 has have AUX cana-3976 45 11 been be AUX cana-3976 45 12 extensively extensively ADV cana-3976 45 13 researched research VERB cana-3976 45 14 and and CCONJ cana-3976 45 15 connected connect VERB cana-3976 45 16 to to ADP cana-3976 45 17 a a DET cana-3976 45 18 wide wide ADJ cana-3976 45 19 range range NOUN cana-3976 45 20 of of ADP cana-3976 45 21 difficulties difficulty NOUN cana-3976 45 22 and and CCONJ cana-3976 45 23 challenges challenge NOUN cana-3976 45 24 . . PUNCT cana-3976 46 1 on on ADP cana-3976 46 2 the the DET cana-3976 46 3 other other ADJ cana-3976 46 4 hand hand NOUN cana-3976 46 5 , , PUNCT cana-3976 46 6 there there PRON cana-3976 46 7 have have AUX cana-3976 46 8 recently recently ADV cana-3976 46 9 been be AUX cana-3976 46 10 numerous numerous ADJ cana-3976 46 11 attempts attempt NOUN cana-3976 46 12 to to PART cana-3976 46 13 use use VERB cana-3976 46 14 mri mri NOUN cana-3976 46 15 data datum NOUN cana-3976 46 16 to to PART cana-3976 46 17 diagnose diagnose VERB cana-3976 46 18 . . PUNCT cana-3976 47 1 here here ADV cana-3976 47 2 are be AUX cana-3976 47 3 some some DET cana-3976 47 4 examples example NOUN cana-3976 47 5 of of ADP cana-3976 47 6 work work NOUN cana-3976 47 7 from from ADP cana-3976 47 8 linked link VERB cana-3976 47 9 literature literature NOUN cana-3976 47 10 : : PUNCT cana-3976 47 11 in in ADP cana-3976 47 12 [ [ X cana-3976 47 13 13 13 NUM cana-3976 47 14 ] ] PUNCT cana-3976 47 15 , , PUNCT cana-3976 47 16 the the DET cana-3976 47 17 authors author NOUN cana-3976 47 18 constructed construct VERB cana-3976 47 19 a a DET cana-3976 47 20 new new ADJ cana-3976 47 21 technique technique NOUN cana-3976 47 22 for for ADP cana-3976 47 23 predicting predict VERB cana-3976 47 24 the the DET cana-3976 47 25 progression progression NOUN cana-3976 47 26 of of ADP cana-3976 47 27 mild mild ADJ cana-3976 47 28 cognitive cognitive ADJ cana-3976 47 29 impairment impairment NOUN cana-3976 47 30 ( ( PUNCT cana-3976 47 31 mci mci NOUN cana-3976 47 32 ) ) PUNCT cana-3976 47 33 using use VERB cana-3976 47 34 mri mri NOUN cana-3976 47 35 . . PUNCT cana-3976 48 1 the the DET cana-3976 48 2 initial initial ADJ cana-3976 48 3 step step NOUN cana-3976 48 4 for for ADP cana-3976 48 5 the the DET cana-3976 48 6 researchers researcher NOUN cana-3976 48 7 was be AUX cana-3976 48 8 to to PART cana-3976 48 9 apply apply VERB cana-3976 48 10 semi semi ADJ cana-3976 48 11 - - ADJ cana-3976 48 12 supervised supervised ADJ cana-3976 48 13 learning learning NOUN cana-3976 48 14 to to PART cana-3976 48 15 generate generate VERB cana-3976 48 16 mri mri NOUN cana-3976 48 17 biomarker biomarker NOUN cana-3976 48 18 progression progression NOUN cana-3976 48 19 . . PUNCT cana-3976 49 1 they they PRON cana-3976 49 2 next next ADV cana-3976 49 3 employed employ VERB cana-3976 49 4 supervised supervised ADJ cana-3976 49 5 learning learn VERB cana-3976 49 6 to to PART cana-3976 49 7 connect connect VERB cana-3976 49 8 this this DET cana-3976 49 9 biomarker biomarker NOUN cana-3976 49 10 to to ADP cana-3976 49 11 the the DET cana-3976 49 12 subjects subject NOUN cana-3976 49 13 ' ' PART cana-3976 49 14 ages age NOUN cana-3976 49 15 and and CCONJ cana-3976 49 16 cognitive cognitive ADJ cana-3976 49 17 skills skill NOUN cana-3976 49 18 . . PUNCT cana-3976 50 1 they they PRON cana-3976 50 2 eventually eventually ADV cana-3976 50 3 decided decide VERB cana-3976 50 4 to to PART cana-3976 50 5 make make VERB cana-3976 50 6 their their PRON cana-3976 50 7 findings finding NOUN cana-3976 50 8 public public ADJ cana-3976 50 9 . . PUNCT cana-3976 51 1 they they PRON cana-3976 51 2 list list VERB cana-3976 51 3 some some DET cana-3976 51 4 unique unique ADJ cana-3976 51 5 elements element NOUN cana-3976 51 6 uncovered uncover VERB cana-3976 51 7 by by ADP cana-3976 51 8 various various ADJ cana-3976 51 9 biomarker biomarker NOUN cana-3976 51 10 learning learn VERB cana-3976 51 11 approaches approach NOUN cana-3976 51 12 below below ADP cana-3976 51 13 1 1 NUM cana-3976 51 14 ) ) PUNCT cana-3976 51 15 mri mri NOUN cana-3976 51 16 biomarker biomarker NOUN cana-3976 51 17 development development NOUN cana-3976 51 18 using use VERB cana-3976 51 19 semi semi ADJ cana-3976 51 20 - - ADJ cana-3976 51 21 supervised supervised ADJ cana-3976 51 22 learning learning NOUN cana-3976 51 23 against against ADP cana-3976 51 24 more more ADJ cana-3976 51 25 communications communication NOUN cana-3976 51 26 on on ADP cana-3976 51 27 applied apply VERB cana-3976 51 28 nonlinear nonlinear ADJ cana-3976 51 29 analysis analysis NOUN cana-3976 51 30 issn issn NOUN cana-3976 51 31 : : PUNCT cana-3976 51 32 1074 1074 NUM cana-3976 51 33 - - PUNCT cana-3976 51 34 133x 133x NUM cana-3976 51 35 vol vol NOUN cana-3976 51 36 32 32 NUM cana-3976 51 37 no no NOUN cana-3976 51 38 . . PUNCT cana-3976 52 1 9s 9s NUM cana-3976 52 2 ( ( PUNCT cana-3976 52 3 2025 2025 NUM cana-3976 52 4 ) ) PUNCT cana-3976 52 5 704 704 NUM cana-3976 52 6 https://internationalpubls.com https://internationalpubls.com X cana-3976 52 7 standard standard ADJ cana-3976 52 8 supervised supervised ADJ cana-3976 52 9 methods method NOUN cana-3976 52 10 ; ; PUNCT cana-3976 52 11 2 2 X cana-3976 52 12 ) ) PUNCT cana-3976 52 13 mri mri NOUN cana-3976 52 14 biomarker biomarker NOUN cana-3976 52 15 development development NOUN cana-3976 52 16 using use VERB cana-3976 52 17 a a DET cana-3976 52 18 semi semi ADJ cana-3976 52 19 - - ADJ cana-3976 52 20 supervised supervised ADJ cana-3976 52 21 learning learning NOUN cana-3976 52 22 strategy strategy NOUN cana-3976 52 23 . . PUNCT cana-3976 53 1 to to PART cana-3976 53 2 avoid avoid VERB cana-3976 53 3 potential potential ADJ cana-3976 53 4 ad ad NOUN cana-3976 53 5 , , PUNCT cana-3976 53 6 they they PRON cana-3976 53 7 removed remove VERB cana-3976 53 8 aging age VERB cana-3976 53 9 effects effect NOUN cana-3976 53 10 from from ADP cana-3976 53 11 the the DET cana-3976 53 12 mri mri NOUN cana-3976 53 13 data datum NOUN cana-3976 53 14 before before ADP cana-3976 53 15 classifier classifier NOUN cana-3976 53 16 training training NOUN cana-3976 53 17 , , PUNCT cana-3976 53 18 and and CCONJ cana-3976 53 19 feature feature NOUN cana-3976 53 20 selection selection NOUN cana-3976 53 21 was be AUX cana-3976 53 22 performed perform VERB cana-3976 53 23 on on ADP cana-3976 53 24 ad ad NOUN cana-3976 53 25 subjects subject NOUN cana-3976 53 26 . . PUNCT cana-3976 54 1 according accord VERB cana-3976 54 2 to to ADP cana-3976 54 3 the the DET cana-3976 54 4 study study NOUN cana-3976 54 5 's 's PART cana-3976 54 6 findings finding NOUN cana-3976 54 7 , , PUNCT cana-3976 54 8 the the DET cana-3976 54 9 proposed propose VERB cana-3976 54 10 method method NOUN cana-3976 54 11 may may AUX cana-3976 54 12 be be AUX cana-3976 54 13 nominal nominal ADJ cana-3976 54 14 for for ADP cana-3976 54 15 early early ADJ cana-3976 54 16 ad ad NOUN cana-3976 54 17 detection detection NOUN cana-3976 54 18 and and CCONJ cana-3976 54 19 for for ADP cana-3976 54 20 mri mri NOUN cana-3976 54 21 in in ADP cana-3976 54 22 predicting predict VERB cana-3976 54 23 whether whether SCONJ cana-3976 54 24 mci mci PROPN cana-3976 54 25 will will AUX cana-3976 54 26 develop develop VERB cana-3976 54 27 into into ADP cana-3976 54 28 ad ad NOUN cana-3976 54 29 . . PUNCT cana-3976 55 1 in in ADP cana-3976 55 2 [ [ X cana-3976 55 3 14 14 NUM cana-3976 55 4 ] ] PUNCT cana-3976 55 5 , , PUNCT cana-3976 55 6 the the DET cana-3976 55 7 authors author NOUN cana-3976 55 8 described describe VERB cana-3976 55 9 a a DET cana-3976 55 10 computer computer NOUN cana-3976 55 11 - - PUNCT cana-3976 55 12 aided aid VERB cana-3976 55 13 diagnostic diagnostic ADJ cana-3976 55 14 ( ( PUNCT cana-3976 55 15 cad cad NOUN cana-3976 55 16 ) ) PUNCT cana-3976 55 17 system system NOUN cana-3976 55 18 for for ADP cana-3976 55 19 mri mri NOUN cana-3976 55 20 brain brain NOUN cana-3976 55 21 imaging imaging NOUN cana-3976 55 22 . . PUNCT cana-3976 56 1 they they PRON cana-3976 56 2 would would AUX cana-3976 56 3 build build VERB cana-3976 56 4 the the DET cana-3976 56 5 system system NOUN cana-3976 56 6 using use VERB cana-3976 56 7 eigen eigen PROPN cana-3976 56 8 brains brain NOUN cana-3976 56 9 and and CCONJ cana-3976 56 10 machine machine NOUN cana-3976 56 11 learning learning NOUN cana-3976 56 12 , , PUNCT cana-3976 56 13 with with ADP cana-3976 56 14 two two NUM cana-3976 56 15 goals goal NOUN cana-3976 56 16 in in ADP cana-3976 56 17 mind mind NOUN cana-3976 56 18 : : PUNCT cana-3976 56 19 reliably reliably ADV cana-3976 56 20 recognizing recognize VERB cana-3976 56 21 alzheimer alzheimer PROPN cana-3976 56 22 's 's PART cana-3976 56 23 disease disease NOUN cana-3976 56 24 patients patient NOUN cana-3976 56 25 and and CCONJ cana-3976 56 26 identifying identify VERB cana-3976 56 27 ad ad NOUN cana-3976 56 28 - - PUNCT cana-3976 56 29 related relate VERB cana-3976 56 30 brain brain NOUN cana-3976 56 31 areas area NOUN cana-3976 56 32 . . PUNCT cana-3976 57 1 to to PART cana-3976 57 2 begin begin VERB cana-3976 57 3 , , PUNCT cana-3976 57 4 3d 3d NUM cana-3976 57 5 volumetric volumetric NOUN cana-3976 57 6 data datum NOUN cana-3976 57 7 is be AUX cana-3976 57 8 subjected subject VERB cana-3976 57 9 to to ADP cana-3976 57 10 the the DET cana-3976 57 11 maximum maximum ADJ cana-3976 57 12 inter inter ADJ cana-3976 57 13 - - ADJ cana-3976 57 14 class class ADJ cana-3976 57 15 variance variance NOUN cana-3976 57 16 ( ( PUNCT cana-3976 57 17 icv icv PROPN cana-3976 57 18 ) ) PUNCT cana-3976 57 19 to to PART cana-3976 57 20 choose choose VERB cana-3976 57 21 essential essential ADJ cana-3976 57 22 slices slice NOUN cana-3976 57 23 for for ADP cana-3976 57 24 subsequent subsequent ADJ cana-3976 57 25 analysis analysis NOUN cana-3976 57 26 . . PUNCT cana-3976 58 1 the the DET cana-3976 58 2 following follow VERB cana-3976 58 3 step step NOUN cana-3976 58 4 is be AUX cana-3976 58 5 for for SCONJ cana-3976 58 6 each each DET cana-3976 58 7 participant participant NOUN cana-3976 58 8 to to PART cana-3976 58 9 create create VERB cana-3976 58 10 an an DET cana-3976 58 11 eigenbrain eigenbrain NOUN cana-3976 58 12 set set NOUN cana-3976 58 13 . . PUNCT cana-3976 59 1 the the DET cana-3976 59 2 most most ADV cana-3976 59 3 critical critical ADJ cana-3976 59 4 eigenbrain eigenbrain NOUN cana-3976 59 5 , , PUNCT cana-3976 59 6 the the DET cana-3976 59 7 mie mie PROPN cana-3976 59 8 , , PUNCT cana-3976 59 9 was be AUX cana-3976 59 10 discovered discover VERB cana-3976 59 11 using use VERB cana-3976 59 12 welch welch PROPN cana-3976 59 13 's 's PART cana-3976 59 14 t t PROPN cana-3976 59 15 - - PUNCT cana-3976 59 16 test test NOUN cana-3976 59 17 , , PUNCT cana-3976 59 18 also also ADV cana-3976 59 19 known know VERB cana-3976 59 20 as as ADP cana-3976 59 21 the the DET cana-3976 59 22 wtt wtt PROPN cana-3976 59 23 . . PUNCT cana-3976 60 1 finally finally ADV cana-3976 60 2 , , PUNCT cana-3976 60 3 different different ADJ cana-3976 60 4 kernels kernel NOUN cana-3976 60 5 were be AUX cana-3976 60 6 employed employ VERB cana-3976 60 7 in in ADP cana-3976 60 8 kernel kernel PROPN cana-3976 60 9 support support NOUN cana-3976 60 10 vector vector NOUN cana-3976 60 11 computers computer NOUN cana-3976 60 12 to to PART cana-3976 60 13 forecast forecast VERB cana-3976 60 14 alzheimer alzheimer PROPN cana-3976 60 15 's 's PART cana-3976 60 16 disease disease NOUN cana-3976 60 17 patients patient NOUN cana-3976 60 18 correctly correctly ADV cana-3976 60 19 . . PUNCT cana-3976 61 1 particle particle NOUN cana-3976 61 2 swarm swarm NOUN cana-3976 61 3 optimization optimization NOUN cana-3976 61 4 was be AUX cana-3976 61 5 used use VERB cana-3976 61 6 to to PART cana-3976 61 7 train train VERB cana-3976 61 8 these these DET cana-3976 61 9 machines machine NOUN cana-3976 61 10 . . PUNCT cana-3976 62 1 we we PRON cana-3976 62 2 focused focus VERB cana-3976 62 3 on on ADP cana-3976 62 4 mie mie PROPN cana-3976 62 5 coefficients coefficient NOUN cana-3976 62 6 with with ADP cana-3976 62 7 values value NOUN cana-3976 62 8 greater great ADJ cana-3976 62 9 than than ADP cana-3976 62 10 0.98 0.98 NUM cana-3976 62 11 quantiles quantile NOUN cana-3976 62 12 to to PART cana-3976 62 13 determine determine VERB cana-3976 62 14 the the DET cana-3976 62 15 discriminant discriminant ADJ cana-3976 62 16 areas area NOUN cana-3976 62 17 that that PRON cana-3976 62 18 discriminate discriminate VERB cana-3976 62 19 ad ad NOUN cana-3976 62 20 from from ADP cana-3976 62 21 nc nc PROPN cana-3976 62 22 . . PUNCT cana-3976 63 1 the the DET cana-3976 63 2 study study NOUN cana-3976 63 3 's 's PART cana-3976 63 4 findings finding NOUN cana-3976 63 5 revealed reveal VERB cana-3976 63 6 that that SCONJ cana-3976 63 7 the the DET cana-3976 63 8 proposed propose VERB cana-3976 63 9 method method NOUN cana-3976 63 10 might might AUX cana-3976 63 11 predict predict VERB cana-3976 63 12 ad ad NOUN cana-3976 63 13 patients patient NOUN cana-3976 63 14 with with ADP cana-3976 63 15 the the DET cana-3976 63 16 same same ADJ cana-3976 63 17 accuracy accuracy NOUN cana-3976 63 18 as as ADP cana-3976 63 19 existing exist VERB cana-3976 63 20 methods method NOUN cana-3976 63 21 . . PUNCT cana-3976 64 1 in in ADP cana-3976 64 2 [ [ X cana-3976 64 3 15 15 NUM cana-3976 64 4 ] ] PUNCT cana-3976 64 5 , , PUNCT cana-3976 64 6 the the DET cana-3976 64 7 authors author NOUN cana-3976 64 8 utilized utilize VERB cana-3976 64 9 mathematical mathematical ADJ cana-3976 64 10 models model NOUN cana-3976 64 11 to to PART cana-3976 64 12 discover discover VERB cana-3976 64 13 potential potential ADJ cana-3976 64 14 brain brain NOUN cana-3976 64 15 locations location NOUN cana-3976 64 16 associated associate VERB cana-3976 64 17 with with ADP cana-3976 64 18 alzheimer alzheimer PROPN cana-3976 64 19 's 's PART cana-3976 64 20 disease disease NOUN cana-3976 64 21 . . PUNCT cana-3976 65 1 twenty twenty NUM cana-3976 65 2 patients patient NOUN cana-3976 65 3 had have VERB cana-3976 65 4 alzheimer alzheimer PROPN cana-3976 65 5 's 's PART cana-3976 65 6 disease disease NOUN cana-3976 65 7 , , PUNCT cana-3976 65 8 with with ADP cana-3976 65 9 the the DET cana-3976 65 10 remaining remain VERB cana-3976 65 11 13 13 NUM cana-3976 65 12 being be AUX cana-3976 65 13 healthy healthy ADJ cana-3976 65 14 controls control NOUN cana-3976 65 15 . . PUNCT cana-3976 66 1 to to PART cana-3976 66 2 begin begin VERB cana-3976 66 3 , , PUNCT cana-3976 66 4 they they PRON cana-3976 66 5 built build VERB cana-3976 66 6 the the DET cana-3976 66 7 brain brain NOUN cana-3976 66 8 's 's PART cana-3976 66 9 structural structural ADJ cana-3976 66 10 network network NOUN cana-3976 66 11 using use VERB cana-3976 66 12 a a DET cana-3976 66 13 technique technique NOUN cana-3976 66 14 known know VERB cana-3976 66 15 as as ADP cana-3976 66 16 diffusion diffusion NOUN cana-3976 66 17 tensor tensor NOUN cana-3976 66 18 imaging imaging NOUN cana-3976 66 19 , , PUNCT cana-3976 66 20 or or CCONJ cana-3976 66 21 dti dti PROPN cana-3976 66 22 . . PROPN cana-3976 67 1 unlike unlike ADP cana-3976 67 2 graph graph NOUN cana-3976 67 3 theory theory NOUN cana-3976 67 4 , , PUNCT cana-3976 67 5 the the DET cana-3976 67 6 2hop 2hop NUM cana-3976 67 7 - - PUNCT cana-3976 67 8 connectivity connectivity NOUN cana-3976 67 9 measure measure NOUN cana-3976 67 10 employs employ VERB cana-3976 67 11 higher high ADJ cana-3976 67 12 - - PUNCT cana-3976 67 13 order order NOUN cana-3976 67 14 data datum NOUN cana-3976 67 15 within within ADP cana-3976 67 16 the the DET cana-3976 67 17 network network NOUN cana-3976 67 18 topology topology NOUN cana-3976 67 19 . . PUNCT cana-3976 68 1 to to PART cana-3976 68 2 accomplish accomplish VERB cana-3976 68 3 this this DET cana-3976 68 4 goal goal NOUN cana-3976 68 5 , , PUNCT cana-3976 68 6 the the DET cana-3976 68 7 authors author NOUN cana-3976 68 8 devised devise VERB cana-3976 68 9 a a DET cana-3976 68 10 novel novel ADJ cana-3976 68 11 method method NOUN cana-3976 68 12 called call VERB cana-3976 68 13 2hoprwr 2hoprwr NUM cana-3976 68 14 , , PUNCT cana-3976 68 15 an an DET cana-3976 68 16 algorithm algorithm NOUN cana-3976 68 17 for for ADP cana-3976 68 18 measuring measure VERB cana-3976 68 19 two two NUM cana-3976 68 20 - - PUNCT cana-3976 68 21 hop hop NOUN cana-3976 68 22 connections connection NOUN cana-3976 68 23 . . PUNCT cana-3976 69 1 the the DET cana-3976 69 2 global global ADJ cana-3976 69 3 feature feature NOUN cana-3976 69 4 score score NOUN cana-3976 69 5 ( ( PUNCT cana-3976 69 6 gfs gfs NOUN cana-3976 69 7 ) ) PUNCT cana-3976 69 8 is be AUX cana-3976 69 9 an an DET cana-3976 69 10 innovative innovative ADJ cana-3976 69 11 approach approach NOUN cana-3976 69 12 for for ADP cana-3976 69 13 the the DET cana-3976 69 14 link link NOUN cana-3976 69 15 evaluating evaluating NOUN cana-3976 69 16 which which DET cana-3976 69 17 brain brain NOUN cana-3976 69 18 regions region NOUN cana-3976 69 19 to to ADP cana-3976 69 20 alzheimer alzheimer PROPN cana-3976 69 21 's 's PART cana-3976 69 22 disease disease NOUN cana-3976 69 23 ( ( PUNCT cana-3976 69 24 ad ad NOUN cana-3976 69 25 ) ) PUNCT cana-3976 69 26 . . PUNCT cana-3976 70 1 the the DET cana-3976 70 2 gfs gfs PROPN cana-3976 70 3 was be AUX cana-3976 70 4 designed design VERB cana-3976 70 5 to to PART cana-3976 70 6 provide provide VERB cana-3976 70 7 an an DET cana-3976 70 8 answer answer NOUN cana-3976 70 9 to to ADP cana-3976 70 10 this this DET cana-3976 70 11 question question NOUN cana-3976 70 12 . . PUNCT cana-3976 71 1 this this DET cana-3976 71 2 score score NOUN cana-3976 71 3 was be AUX cana-3976 71 4 derived derive VERB cana-3976 71 5 by by ADP cana-3976 71 6 combining combine VERB cana-3976 71 7 five five NUM cana-3976 71 8 distinct distinct ADJ cana-3976 71 9 local local ADJ cana-3976 71 10 features feature NOUN cana-3976 71 11 : : PUNCT cana-3976 71 12 degree degree NOUN cana-3976 71 13 centrality centrality NOUN cana-3976 71 14 , , PUNCT cana-3976 71 15 closeness closeness NOUN cana-3976 71 16 centrality centrality NOUN cana-3976 71 17 , , PUNCT cana-3976 71 18 maximal maximal ADJ cana-3976 71 19 clique clique NOUN cana-3976 71 20 number number NOUN cana-3976 71 21 , , PUNCT cana-3976 71 22 and and CCONJ cana-3976 71 23 2hop 2hop NUM cana-3976 71 24 connectivity connectivity NOUN cana-3976 71 25 . . PUNCT cana-3976 72 1 finally finally ADV cana-3976 72 2 , , PUNCT cana-3976 72 3 a a DET cana-3976 72 4 canonical canonical ADJ cana-3976 72 5 correlation correlation NOUN cana-3976 72 6 analysis analysis NOUN cana-3976 72 7 revealed reveal VERB cana-3976 72 8 a a DET cana-3976 72 9 high high ADJ cana-3976 72 10 link link NOUN cana-3976 72 11 between between ADP cana-3976 72 12 the the DET cana-3976 72 13 gfs gfs PROPN cana-3976 72 14 mmse mmse PROPN cana-3976 72 15 and and CCONJ cana-3976 72 16 moca moca PROPN cana-3976 72 17 scale scale PROPN cana-3976 72 18 findings finding NOUN cana-3976 72 19 . . PUNCT cana-3976 73 1 in in ADP cana-3976 73 2 [ [ X cana-3976 73 3 16 16 NUM cana-3976 73 4 ] ] PUNCT cana-3976 73 5 , , PUNCT cana-3976 73 6 the the DET cana-3976 73 7 authors author NOUN cana-3976 73 8 comprised comprise VERB cana-3976 73 9 three three NUM cana-3976 73 10 key key ADJ cana-3976 73 11 contributions contribution NOUN cana-3976 73 12 to to ADP cana-3976 73 13 these these DET cana-3976 73 14 constraints constraint NOUN cana-3976 73 15 . . PUNCT cana-3976 74 1 they they PRON cana-3976 74 2 began begin VERB cana-3976 74 3 by by ADP cana-3976 74 4 thoroughly thoroughly ADV cana-3976 74 5 reviewing review VERB cana-3976 74 6 existing exist VERB cana-3976 74 7 research research NOUN cana-3976 74 8 . . PUNCT cana-3976 75 1 they they PRON cana-3976 75 2 found find VERB cana-3976 75 3 four four NUM cana-3976 75 4 fundamental fundamental ADJ cana-3976 75 5 techniques technique NOUN cana-3976 75 6 , , PUNCT cana-3976 75 7 which which PRON cana-3976 75 8 are be AUX cana-3976 75 9 as as SCONJ cana-3976 75 10 follows follow VERB cana-3976 75 11 : : PUNCT cana-3976 75 12 there there PRON cana-3976 75 13 are be VERB cana-3976 75 14 four four NUM cana-3976 75 15 categories category NOUN cana-3976 75 16 of of ADP cana-3976 75 17 cnns cnn NOUN cana-3976 75 18 such such ADJ cana-3976 75 19 as as ADP cana-3976 75 20 2d 2d NUM cana-3976 75 21 slice slice NOUN cana-3976 75 22 - - PUNCT cana-3976 75 23 level level NOUN cana-3976 75 24 , , PUNCT cana-3976 75 25 3d 3d NUM cana-3976 75 26 patch patch NOUN cana-3976 75 27 - - PUNCT cana-3976 75 28 level level NOUN cana-3976 75 29 , , PUNCT cana-3976 75 30 roi roi NOUN cana-3976 75 31 - - PUNCT cana-3976 75 32 based base VERB cana-3976 75 33 , , PUNCT cana-3976 75 34 and and CCONJ cana-3976 75 35 3d 3d NUM cana-3976 75 36 subject subject ADJ cana-3976 75 37 - - PUNCT cana-3976 75 38 level level NOUN cana-3976 75 39 , , PUNCT cana-3976 75 40 respectively respectively ADV cana-3976 75 41 . . PUNCT cana-3976 76 1 furthermore furthermore ADV cana-3976 76 2 , , PUNCT cana-3976 76 3 they they PRON cana-3976 76 4 discovered discover VERB cana-3976 76 5 that that SCONJ cana-3976 76 6 more more ADJ cana-3976 76 7 than than ADP cana-3976 76 8 half half NOUN cana-3976 76 9 of of ADP cana-3976 76 10 the the DET cana-3976 76 11 articles article NOUN cana-3976 76 12 reviewed review VERB cana-3976 76 13 could could AUX cana-3976 76 14 have have AUX cana-3976 76 15 been be AUX cana-3976 76 16 impacted impact VERB cana-3976 76 17 by by ADP cana-3976 76 18 data datum NOUN cana-3976 76 19 leaks leak NOUN cana-3976 76 20 , , PUNCT cana-3976 76 21 leading lead VERB cana-3976 76 22 to to ADP cana-3976 76 23 accusations accusation NOUN cana-3976 76 24 of of ADP cana-3976 76 25 biased biased ADJ cana-3976 76 26 performance performance NOUN cana-3976 76 27 . . PUNCT cana-3976 77 1 our our PRON cana-3976 77 2 second second ADJ cana-3976 77 3 contribution contribution NOUN cana-3976 77 4 to to ADP cana-3976 77 5 the the DET cana-3976 77 6 field field NOUN cana-3976 77 7 improved improve VERB cana-3976 77 8 our our PRON cana-3976 77 9 open open ADJ cana-3976 77 10 - - PUNCT cana-3976 77 11 source source NOUN cana-3976 77 12 method method NOUN cana-3976 77 13 for for ADP cana-3976 77 14 diagnosing diagnose VERB cana-3976 77 15 alzheimer alzheimer NOUN cana-3976 77 16 's 's PART cana-3976 77 17 disease disease NOUN cana-3976 77 18 using use VERB cana-3976 77 19 cnn cnn PROPN cana-3976 77 20 and and CCONJ cana-3976 77 21 t1 t1 NOUN cana-3976 77 22 - - PUNCT cana-3976 77 23 weighted weight VERB cana-3976 77 24 mri mri NOUN cana-3976 77 25 . . PUNCT cana-3976 78 1 a a DET cana-3976 78 2 modular modular ADJ cana-3976 78 3 set set NOUN cana-3976 78 4 of of ADP cana-3976 78 5 deep deep ADJ cana-3976 78 6 learning learning NOUN cana-3976 78 7 - - PUNCT cana-3976 78 8 specific specific ADJ cana-3976 78 9 picture picture NOUN cana-3976 78 10 preparation preparation NOUN cana-3976 78 11 methods method NOUN cana-3976 78 12 , , PUNCT cana-3976 78 13 classification classification NOUN cana-3976 78 14 systems system NOUN cana-3976 78 15 , , PUNCT cana-3976 78 16 and and CCONJ cana-3976 78 17 assessment assessment NOUN cana-3976 78 18 procedures procedure NOUN cana-3976 78 19 is be AUX cana-3976 78 20 supplied supply VERB cana-3976 78 21 in in ADP cana-3976 78 22 addition addition NOUN cana-3976 78 23 to to ADP cana-3976 78 24 pre pre ADJ cana-3976 78 25 - - ADJ cana-3976 78 26 existing existing ADJ cana-3976 78 27 tools tool NOUN cana-3976 78 28 for for ADP cana-3976 78 29 automatically automatically ADV cana-3976 78 30 transforming transform VERB cana-3976 78 31 data datum NOUN cana-3976 78 32 . . PUNCT cana-3976 79 1 finally finally ADV cana-3976 79 2 , , PUNCT cana-3976 79 3 they they PRON cana-3976 79 4 tested test VERB cana-3976 79 5 the the DET cana-3976 79 6 strategy strategy NOUN cana-3976 79 7 by by ADP cana-3976 79 8 carefully carefully ADV cana-3976 79 9 examining examine VERB cana-3976 79 10 numerous numerous ADJ cana-3976 79 11 cnn cnn PROPN cana-3976 79 12 design design NOUN cana-3976 79 13 backgrounds background NOUN cana-3976 79 14 . . PUNCT cana-3976 80 1 in in ADP cana-3976 80 2 [ [ X cana-3976 80 3 17 17 NUM cana-3976 80 4 ] ] PUNCT cana-3976 80 5 , , PUNCT cana-3976 80 6 the the DET cana-3976 80 7 author author NOUN cana-3976 80 8 aimed aim VERB cana-3976 80 9 to to PART cana-3976 80 10 explore explore VERB cana-3976 80 11 if if SCONJ cana-3976 80 12 multi multi ADJ cana-3976 80 13 - - ADJ cana-3976 80 14 parameter parameter ADJ cana-3976 80 15 structural structural ADJ cana-3976 80 16 mri mri NOUN cana-3976 80 17 features feature NOUN cana-3976 80 18 were be AUX cana-3976 80 19 employed employ VERB cana-3976 80 20 as as ADP cana-3976 80 21 a a DET cana-3976 80 22 meaningful meaningful ADJ cana-3976 80 23 biomarker biomarker NOUN cana-3976 80 24 for for ADP cana-3976 80 25 distinguishing distinguish VERB cana-3976 80 26 between between ADP cana-3976 80 27 vasculovascular vasculovascular ADJ cana-3976 80 28 disease disease NOUN cana-3976 80 29 and and CCONJ cana-3976 80 30 alzheimer alzheimer PROPN cana-3976 80 31 's 's PART cana-3976 80 32 disease disease NOUN cana-3976 80 33 . . PUNCT cana-3976 81 1 methods method NOUN cana-3976 81 2 : : PUNCT cana-3976 81 3 between between ADP cana-3976 81 4 june june PROPN cana-3976 81 5 2013 2013 NUM cana-3976 81 6 and and CCONJ cana-3976 81 7 july july PROPN cana-3976 81 8 2019 2019 NUM cana-3976 81 9 , , PUNCT cana-3976 81 10 93 93 NUM cana-3976 81 11 people people NOUN cana-3976 81 12 participated participate VERB cana-3976 81 13 in in ADP cana-3976 81 14 this this DET cana-3976 81 15 study study NOUN cana-3976 81 16 . . PUNCT cana-3976 82 1 all all PRON cana-3976 82 2 of of ADP cana-3976 82 3 them they PRON cana-3976 82 4 were be AUX cana-3976 82 5 diagnosed diagnose VERB cana-3976 82 6 with with ADP cana-3976 82 7 alzheimer alzheimer PROPN cana-3976 82 8 's 's PART cana-3976 82 9 disease disease NOUN cana-3976 82 10 or or CCONJ cana-3976 82 11 vasculocortical vasculocortical ADJ cana-3976 82 12 dementia dementia NOUN cana-3976 82 13 , , PUNCT cana-3976 82 14 verified verify VERB cana-3976 82 15 by by ADP cana-3976 82 16 two two NUM cana-3976 82 17 chief chief ADJ cana-3976 82 18 physicians physician NOUN cana-3976 82 19 . . PUNCT cana-3976 83 1 communications communication NOUN cana-3976 83 2 on on ADP cana-3976 83 3 applied apply VERB cana-3976 83 4 nonlinear nonlinear ADJ cana-3976 83 5 analysis analysis NOUN cana-3976 83 6 issn issn NOUN cana-3976 83 7 : : PUNCT cana-3976 83 8 1074 1074 NUM cana-3976 83 9 - - PUNCT cana-3976 83 10 133x 133x NUM cana-3976 83 11 vol vol NOUN cana-3976 83 12 32 32 NUM cana-3976 83 13 no no NOUN cana-3976 83 14 . . PUNCT cana-3976 84 1 9s 9s NUM cana-3976 84 2 ( ( PUNCT cana-3976 84 3 2025 2025 NUM cana-3976 84 4 ) ) PUNCT cana-3976 84 5 705 705 NUM cana-3976 84 6 https://internationalpubls.com https://internationalpubls.com X cana-3976 84 7 the the DET cana-3976 84 8 accubrain accubrain NOUN cana-3976 84 9 system system NOUN cana-3976 84 10 could could AUX cana-3976 84 11 get get VERB cana-3976 84 12 multi multi ADJ cana-3976 84 13 - - ADJ cana-3976 84 14 parameter parameter ADJ cana-3976 84 15 volumetric volumetric NOUN cana-3976 84 16 measurements measurement NOUN cana-3976 84 17 from from ADP cana-3976 84 18 various various ADJ cana-3976 84 19 brain brain NOUN cana-3976 84 20 regions region NOUN cana-3976 84 21 using use VERB cana-3976 84 22 automated automate VERB cana-3976 84 23 brain brain NOUN cana-3976 84 24 tissue tissue NOUN cana-3976 84 25 segmentation segmentation NOUN cana-3976 84 26 . . PUNCT cana-3976 85 1 to to PART cana-3976 85 2 minimize minimize VERB cana-3976 85 3 dimensionality dimensionality NOUN cana-3976 85 4 , , PUNCT cana-3976 85 5 they they PRON cana-3976 85 6 explored explore VERB cana-3976 85 7 62 62 NUM cana-3976 85 8 structural structural ADJ cana-3976 85 9 mri mri NOUN cana-3976 85 10 biomarkers biomarker NOUN cana-3976 85 11 to to PART cana-3976 85 12 find find VERB cana-3976 85 13 features feature NOUN cana-3976 85 14 that that PRON cana-3976 85 15 differed differ VERB cana-3976 85 16 significantly significantly ADV cana-3976 85 17 between between ADP cana-3976 85 18 vad vad PROPN cana-3976 85 19 and and CCONJ cana-3976 85 20 ad ad NOUN cana-3976 85 21 . . PUNCT cana-3976 86 1 they they PRON cana-3976 86 2 did do VERB cana-3976 86 3 this this PRON cana-3976 86 4 to to PART cana-3976 86 5 understand understand VERB cana-3976 86 6 the the DET cana-3976 86 7 relationship relationship NOUN cana-3976 86 8 between between ADP cana-3976 86 9 the the DET cana-3976 86 10 two two NUM cana-3976 86 11 illnesses illness NOUN cana-3976 86 12 better well ADV cana-3976 86 13 . . PUNCT cana-3976 87 1 however however ADV cana-3976 87 2 , , PUNCT cana-3976 87 3 lasso lasso NOUN cana-3976 87 4 is be AUX cana-3976 87 5 employed employ VERB cana-3976 87 6 in in ADP cana-3976 87 7 creating create VERB cana-3976 87 8 feature feature NOUN cana-3976 87 9 sets set NOUN cana-3976 87 10 and and CCONJ cana-3976 87 11 other other ADJ cana-3976 87 12 methods method NOUN cana-3976 87 13 . . PUNCT cana-3976 88 1 they they PRON cana-3976 88 2 employed employ VERB cana-3976 88 3 the the DET cana-3976 88 4 feature feature NOUN cana-3976 88 5 collection collection NOUN cana-3976 88 6 using use VERB cana-3976 88 7 svm svm PROPN cana-3976 88 8 . . PROPN cana-3976 88 9 to to PART cana-3976 88 10 determine determine VERB cana-3976 88 11 whether whether SCONJ cana-3976 88 12 one one NUM cana-3976 88 13 classification classification NOUN cana-3976 88 14 model model NOUN cana-3976 88 15 is be AUX cana-3976 88 16 superior superior ADJ cana-3976 88 17 to to ADP cana-3976 88 18 another another PRON cana-3976 88 19 in in ADP cana-3976 88 20 vad vad PROPN cana-3976 88 21 and and CCONJ cana-3976 88 22 ad ad NOUN cana-3976 88 23 , , PUNCT cana-3976 88 24 a a DET cana-3976 88 25 comparison comparison NOUN cana-3976 88 26 analysis analysis NOUN cana-3976 88 27 using use VERB cana-3976 88 28 several several ADJ cana-3976 88 29 machine machine NOUN cana-3976 88 30 learning learning NOUN cana-3976 88 31 algorithms algorithm NOUN cana-3976 88 32 was be AUX cana-3976 88 33 performed perform VERB cana-3976 88 34 and and CCONJ cana-3976 88 35 used use VERB cana-3976 88 36 for for ADP cana-3976 88 37 the the DET cana-3976 88 38 study study NOUN cana-3976 88 39 . . PUNCT cana-3976 89 1 they they PRON cana-3976 89 2 did do VERB cana-3976 89 3 this this PRON cana-3976 89 4 to to PART cana-3976 89 5 ensure ensure VERB cana-3976 89 6 that that SCONJ cana-3976 89 7 the the DET cana-3976 89 8 model model NOUN cana-3976 89 9 's 's PART cana-3976 89 10 performance performance NOUN cana-3976 89 11 was be AUX cana-3976 89 12 evaluated evaluate VERB cana-3976 89 13 objectively objectively ADV cana-3976 89 14 . . PUNCT cana-3976 90 1 in in ADP cana-3976 90 2 [ [ X cana-3976 90 3 18 18 NUM cana-3976 90 4 ] ] PUNCT cana-3976 90 5 , , PUNCT cana-3976 90 6 the the DET cana-3976 90 7 authors author NOUN cana-3976 90 8 described describe VERB cana-3976 90 9 a a DET cana-3976 90 10 method method NOUN cana-3976 90 11 for for ADP cana-3976 90 12 detecting detect VERB cana-3976 90 13 images image NOUN cana-3976 90 14 that that PRON cana-3976 90 15 employs employ VERB cana-3976 90 16 an an DET cana-3976 90 17 effective effective ADJ cana-3976 90 18 transfer transfer NOUN cana-3976 90 19 learning learn VERB cana-3976 90 20 strategy strategy NOUN cana-3976 90 21 by by ADP cana-3976 90 22 fine fine ADV cana-3976 90 23 - - PUNCT cana-3976 90 24 tuning tune VERB cana-3976 90 25 alexnet alexnet NOUN cana-3976 90 26 , , PUNCT cana-3976 90 27 a a DET cana-3976 90 28 pre pre ADJ cana-3976 90 29 - - ADJ cana-3976 90 30 trained train VERB cana-3976 90 31 neural neural ADJ cana-3976 90 32 network network NOUN cana-3976 90 33 . . PUNCT cana-3976 91 1 the the DET cana-3976 91 2 network network NOUN cana-3976 91 3 's 's PART cana-3976 91 4 settings setting NOUN cana-3976 91 5 constructed construct VERB cana-3976 91 6 this this DET cana-3976 91 7 system system NOUN cana-3976 91 8 . . PUNCT cana-3976 92 1 they they PRON cana-3976 92 2 did do VERB cana-3976 92 3 this this PRON cana-3976 92 4 to to PART cana-3976 92 5 aid aid VERB cana-3976 92 6 in in ADP cana-3976 92 7 the the DET cana-3976 92 8 system system NOUN cana-3976 92 9 's 's PART cana-3976 92 10 development development NOUN cana-3976 92 11 . . PUNCT cana-3976 93 1 the the DET cana-3976 93 2 construction construction NOUN cana-3976 93 3 uses use VERB cana-3976 93 4 grey grey PROPN cana-3976 93 5 , , PUNCT cana-3976 93 6 white white ADJ cana-3976 93 7 , , PUNCT cana-3976 93 8 and and CCONJ cana-3976 93 9 cerebral cerebral ADJ cana-3976 93 10 spinal spinal ADJ cana-3976 93 11 fluid fluid NOUN cana-3976 93 12 images image NOUN cana-3976 93 13 . . PUNCT cana-3976 94 1 the the DET cana-3976 94 2 suggested suggest VERB cana-3976 94 3 system system NOUN cana-3976 94 4 's 's PART cana-3976 94 5 performance performance NOUN cana-3976 94 6 is be AUX cana-3976 94 7 assessed assess VERB cana-3976 94 8 and and CCONJ cana-3976 94 9 evaluated evaluate VERB cana-3976 94 10 using use VERB cana-3976 94 11 data datum NOUN cana-3976 94 12 from from ADP cana-3976 94 13 oasis oasis NOUN cana-3976 94 14 . . PUNCT cana-3976 95 1 the the DET cana-3976 95 2 system system NOUN cana-3976 95 3 performed perform VERB cana-3976 95 4 well well ADV cana-3976 95 5 for for ADP cana-3976 95 6 non non ADJ cana-3976 95 7 - - ADJ cana-3976 95 8 segmented segmented ADJ cana-3976 95 9 picture picture NOUN cana-3976 95 10 multi multi ADJ cana-3976 95 11 - - ADJ cana-3976 95 12 class class ADJ cana-3976 95 13 classification classification NOUN cana-3976 95 14 , , PUNCT cana-3976 95 15 with with ADP cana-3976 95 16 an an DET cana-3976 95 17 overall overall ADJ cana-3976 95 18 accuracy accuracy NOUN cana-3976 95 19 of of ADP cana-3976 95 20 92.85 92.85 NUM cana-3976 95 21 % % NOUN cana-3976 95 22 . . PUNCT cana-3976 96 1 the the DET cana-3976 96 2 system system NOUN cana-3976 96 3 also also ADV cana-3976 96 4 yielded yield VERB cana-3976 96 5 positive positive ADJ cana-3976 96 6 results result NOUN cana-3976 96 7 . . PUNCT cana-3976 97 1 in in ADP cana-3976 97 2 [ [ X cana-3976 97 3 19 19 NUM cana-3976 97 4 ] ] PUNCT cana-3976 97 5 , , PUNCT cana-3976 97 6 the the DET cana-3976 97 7 authors author NOUN cana-3976 97 8 described describe VERB cana-3976 97 9 t1 t1 PROPN cana-3976 97 10 - - PUNCT cana-3976 97 11 weighted weight VERB cana-3976 97 12 mri mri NOUN cana-3976 97 13 , , PUNCT cana-3976 97 14 fdg fdg PROPN cana-3976 97 15 - - PUNCT cana-3976 97 16 pet pet NOUN cana-3976 97 17 , , PUNCT cana-3976 97 18 and and CCONJ cana-3976 97 19 regional regional ADJ cana-3976 97 20 cerebral cerebral ADJ cana-3976 97 21 blood blood NOUN cana-3976 97 22 flow flow NOUN cana-3976 97 23 singlephoton singlephoton PROPN cana-3976 97 24 emission emission NOUN cana-3976 97 25 computed compute VERB cana-3976 97 26 tomography tomography NOUN cana-3976 97 27 ( ( PUNCT cana-3976 97 28 cf cf NOUN cana-3976 97 29 - - PUNCT cana-3976 97 30 spect spect NOUN cana-3976 97 31 ) ) PUNCT cana-3976 97 32 in in ADP cana-3976 97 33 ad ad NOUN cana-3976 97 34 subjects subject NOUN cana-3976 97 35 . . PUNCT cana-3976 98 1 twenty twenty NUM cana-3976 98 2 patients patient NOUN cana-3976 98 3 with with ADP cana-3976 98 4 intermediate intermediate ADJ cana-3976 98 5 alzheimer alzheimer PROPN cana-3976 98 6 's 's PART cana-3976 98 7 disease disease NOUN cana-3976 98 8 and and CCONJ cana-3976 98 9 18 18 NUM cana-3976 98 10 healthy healthy ADJ cana-3976 98 11 older old ADJ cana-3976 98 12 controls control NOUN cana-3976 98 13 had have VERB cana-3976 98 14 t1 t1 NOUN cana-3976 98 15 - - PUNCT cana-3976 98 16 mri mri PROPN cana-3976 98 17 , , PUNCT cana-3976 98 18 fdg fdg PROPN cana-3976 98 19 - - NOUN cana-3976 98 20 pet pet NOUN cana-3976 98 21 , , PUNCT cana-3976 98 22 and and CCONJ cana-3976 98 23 rcbfspect rcbfspect NOUN cana-3976 98 24 scans scan NOUN cana-3976 98 25 . . PUNCT cana-3976 99 1 they they PRON cana-3976 99 2 analyzed analyze VERB cana-3976 99 3 images image NOUN cana-3976 99 4 as as ADP cana-3976 99 5 part part NOUN cana-3976 99 6 of of ADP cana-3976 99 7 the the DET cana-3976 99 8 experiment experiment NOUN cana-3976 99 9 to to PART cana-3976 99 10 generate generate VERB cana-3976 99 11 svm svm ADJ cana-3976 99 12 - - PUNCT cana-3976 99 13 based base VERB cana-3976 99 14 diagnostic diagnostic ADJ cana-3976 99 15 accuracy accuracy NOUN cana-3976 99 16 indices index NOUN cana-3976 99 17 . . PUNCT cana-3976 100 1 researchers researcher NOUN cana-3976 100 2 combined combine VERB cana-3976 100 3 data datum NOUN cana-3976 100 4 from from ADP cana-3976 100 5 the the DET cana-3976 100 6 entire entire ADJ cana-3976 100 7 brain brain NOUN cana-3976 100 8 with with ADP cana-3976 100 9 the the DET cana-3976 100 10 results result NOUN cana-3976 100 11 of of ADP cana-3976 100 12 the the DET cana-3976 100 13 leave leave VERB cana-3976 100 14 - - PUNCT cana-3976 100 15 oneout oneout NOUN cana-3976 100 16 cross cross ADJ cana-3976 100 17 - - ADJ cana-3976 100 18 validation validation ADJ cana-3976 100 19 procedure procedure NOUN cana-3976 100 20 . . PUNCT cana-3976 101 1 pet pet ADJ cana-3976 101 2 and and CCONJ cana-3976 101 3 spect spect ADJ cana-3976 101 4 measurements measurement NOUN cana-3976 101 5 had have VERB cana-3976 101 6 comparable comparable ADJ cana-3976 101 7 precision precision NOUN cana-3976 101 8 and and CCONJ cana-3976 101 9 accuracy accuracy NOUN cana-3976 101 10 . . PUNCT cana-3976 102 1 the the DET cana-3976 102 2 accuracy accuracy NOUN cana-3976 102 3 of of ADP cana-3976 102 4 pet pet ADJ cana-3976 102 5 and and CCONJ cana-3976 102 6 spect spect NOUN cana-3976 102 7 was be AUX cana-3976 102 8 higher high ADJ cana-3976 102 9 than than ADP cana-3976 102 10 that that PRON cana-3976 102 11 of of ADP cana-3976 102 12 t1 t1 PROPN cana-3976 102 13 - - PUNCT cana-3976 102 14 mri mri NOUN cana-3976 102 15 data datum NOUN cana-3976 102 16 analysis analysis NOUN cana-3976 102 17 , , PUNCT cana-3976 102 18 which which PRON cana-3976 102 19 had have VERB cana-3976 102 20 an an DET cana-3976 102 21 auc auc NOUN cana-3976 102 22 of of ADP cana-3976 102 23 0.67 0.67 NUM cana-3976 102 24 . . PUNCT cana-3976 103 1 pet pet ADJ cana-3976 103 2 accuracy accuracy NOUN cana-3976 103 3 varied varied ADJ cana-3976 103 4 between between ADP cana-3976 103 5 68 68 NUM cana-3976 103 6 and and CCONJ cana-3976 103 7 71 71 NUM cana-3976 103 8 % % NOUN cana-3976 103 9 , , PUNCT cana-3976 103 10 while while SCONJ cana-3976 103 11 spect spect ADJ cana-3976 103 12 accuracy accuracy NOUN cana-3976 103 13 ranged range VERB cana-3976 103 14 between between ADP cana-3976 103 15 68 68 NUM cana-3976 103 16 and and CCONJ cana-3976 103 17 74 74 NUM cana-3976 103 18 % % NOUN cana-3976 103 19 . . PUNCT cana-3976 104 1 3 3 X cana-3976 104 2 . . X cana-3976 104 3 materials material NOUN cana-3976 104 4 and and CCONJ cana-3976 104 5 methods method NOUN cana-3976 104 6 early early ADJ cana-3976 104 7 alzheimer alzheimer PROPN cana-3976 104 8 's 's PART cana-3976 104 9 identification identification NOUN cana-3976 104 10 is be AUX cana-3976 104 11 crucial crucial ADJ cana-3976 104 12 for for ADP cana-3976 104 13 decreasing decrease VERB cana-3976 104 14 the the DET cana-3976 104 15 disease disease NOUN cana-3976 104 16 's 's PART cana-3976 104 17 progression progression NOUN cana-3976 104 18 and and CCONJ cana-3976 104 19 preventing prevent VERB cana-3976 104 20 its its PRON cana-3976 104 21 onset onset NOUN cana-3976 104 22 . . PUNCT cana-3976 105 1 the the DET cana-3976 105 2 proposed propose VERB cana-3976 105 3 framework framework NOUN cana-3976 105 4 detects detect NOUN cana-3976 105 5 alzheimer alzheimer PROPN cana-3976 105 6 's 's PART cana-3976 105 7 disease disease NOUN cana-3976 105 8 and and CCONJ cana-3976 105 9 acts act NOUN cana-3976 105 10 as as ADP cana-3976 105 11 a a DET cana-3976 105 12 classification classification NOUN cana-3976 105 13 system system NOUN cana-3976 105 14 for for ADP cana-3976 105 15 the the DET cana-3976 105 16 disease disease NOUN cana-3976 105 17 's 's PART cana-3976 105 18 various various ADJ cana-3976 105 19 stages stage NOUN cana-3976 105 20 . . PUNCT cana-3976 106 1 the the DET cana-3976 106 2 following follow VERB cana-3976 106 3 sections section NOUN cana-3976 106 4 will will AUX cana-3976 106 5 detail detail VERB cana-3976 106 6 the the DET cana-3976 106 7 proposed propose VERB cana-3976 106 8 framework framework NOUN cana-3976 106 9 's 's PART cana-3976 106 10 workflow workflow NOUN cana-3976 106 11 , , PUNCT cana-3976 106 12 preparation preparation NOUN cana-3976 106 13 algorithms algorithm NOUN cana-3976 106 14 , , PUNCT cana-3976 106 15 and and CCONJ cana-3976 106 16 medical medical ADJ cana-3976 106 17 image image NOUN cana-3976 106 18 classification classification NOUN cana-3976 106 19 methods method NOUN cana-3976 106 20 . . PUNCT cana-3976 107 1 in in ADP cana-3976 107 2 diagrammatic diagrammatic ADJ cana-3976 107 3 form form NOUN cana-3976 107 4 , , PUNCT cana-3976 107 5 figure figure NOUN cana-3976 107 6 1 1 NUM cana-3976 107 7 demonstrates demonstrate VERB cana-3976 107 8 the the DET cana-3976 107 9 classification classification NOUN cana-3976 107 10 of of ADP cana-3976 107 11 medical medical ADJ cana-3976 107 12 images image NOUN cana-3976 107 13 . . PUNCT cana-3976 108 1 figure figure NOUN cana-3976 108 2 1 1 NUM cana-3976 108 3 : : PUNCT cana-3976 108 4 overview overview NOUN cana-3976 108 5 of of ADP cana-3976 108 6 the the DET cana-3976 108 7 proposed propose VERB cana-3976 108 8 framework framework NOUN cana-3976 108 9 communications communication NOUN cana-3976 108 10 on on ADP cana-3976 108 11 applied apply VERB cana-3976 108 12 nonlinear nonlinear ADJ cana-3976 108 13 analysis analysis NOUN cana-3976 108 14 issn issn NOUN cana-3976 108 15 : : PUNCT cana-3976 108 16 1074 1074 NUM cana-3976 108 17 - - PUNCT cana-3976 108 18 133x 133x NUM cana-3976 108 19 vol vol NOUN cana-3976 108 20 32 32 NUM cana-3976 109 1 no no NOUN cana-3976 109 2 . . PUNCT cana-3976 110 1 9s 9s NUM cana-3976 110 2 ( ( PUNCT cana-3976 110 3 2025 2025 NUM cana-3976 110 4 ) ) PUNCT cana-3976 110 5 706 706 NUM cana-3976 110 6 https://internationalpubls.com https://internationalpubls.com SYM cana-3976 110 7 3.1 3.1 NUM cana-3976 110 8 machine machine NOUN cana-3976 110 9 learning learning NOUN cana-3976 110 10 approach approach NOUN cana-3976 110 11 : : PUNCT cana-3976 110 12 the the DET cana-3976 110 13 oasis oasis PROPN cana-3976 110 14 dataset dataset NOUN cana-3976 110 15 's 's PART cana-3976 110 16 cross cross ADJ cana-3976 110 17 - - ADJ cana-3976 110 18 sectional sectional ADJ cana-3976 110 19 mri mri NOUN cana-3976 110 20 data datum NOUN cana-3976 110 21 and and CCONJ cana-3976 110 22 longitudinal longitudinal ADJ cana-3976 110 23 data datum NOUN cana-3976 110 24 are be AUX cana-3976 110 25 the the DET cana-3976 110 26 two two NUM cana-3976 110 27 forms form NOUN cana-3976 110 28 of of ADP cana-3976 110 29 information information NOUN cana-3976 110 30 included include VERB cana-3976 110 31 in in ADP cana-3976 110 32 the the DET cana-3976 110 33 dataset dataset NOUN cana-3976 110 34 collection collection NOUN cana-3976 110 35 that that PRON cana-3976 110 36 was be AUX cana-3976 110 37 just just ADV cana-3976 110 38 established establish VERB cana-3976 110 39 here here ADV cana-3976 110 40 . . PUNCT cana-3976 111 1 we we PRON cana-3976 111 2 produced produce VERB cana-3976 111 3 the the DET cana-3976 111 4 resulting result VERB cana-3976 111 5 data datum NOUN cana-3976 111 6 set set VERB cana-3976 111 7 utilizing utilize VERB cana-3976 111 8 information information NOUN cana-3976 111 9 from from ADP cana-3976 111 10 150 150 NUM cana-3976 111 11 people people NOUN cana-3976 111 12 aged age VERB cana-3976 111 13 60 60 NUM cana-3976 111 14 to to PART cana-3976 111 15 96 96 NUM cana-3976 111 16 . . PUNCT cana-3976 112 1 all all DET cana-3976 112 2 participants participant NOUN cana-3976 112 3 were be AUX cana-3976 112 4 scanned scan VERB cana-3976 112 5 simultaneously simultaneously ADV cana-3976 112 6 , , PUNCT cana-3976 112 7 and and CCONJ cana-3976 112 8 every every DET cana-3976 112 9 single single ADJ cana-3976 112 10 subject subject NOUN cana-3976 112 11 was be AUX cana-3976 112 12 right right ADV cana-3976 112 13 - - PUNCT cana-3976 112 14 handed handed ADJ cana-3976 112 15 . . PUNCT cana-3976 113 1 during during ADP cana-3976 113 2 the the DET cana-3976 113 3 preliminary preliminary ADJ cana-3976 113 4 visits visit NOUN cana-3976 113 5 , , PUNCT cana-3976 113 6 72 72 NUM cana-3976 113 7 participants participant NOUN cana-3976 113 8 were be AUX cana-3976 113 9 diagnosed diagnose VERB cana-3976 113 10 as as ADP cana-3976 113 11 not not PART cana-3976 113 12 suffering suffer VERB cana-3976 113 13 from from ADP cana-3976 113 14 dementia dementia NOUN cana-3976 113 15 , , PUNCT cana-3976 113 16 while while SCONJ cana-3976 113 17 64 64 NUM cana-3976 113 18 patients patient NOUN cana-3976 113 19 were be AUX cana-3976 113 20 classified classify VERB cana-3976 113 21 as as ADP cana-3976 113 22 suffering suffer VERB cana-3976 113 23 from from ADP cana-3976 113 24 dementia dementia NOUN cana-3976 113 25 . . PUNCT cana-3976 114 1 however however ADV cana-3976 114 2 , , PUNCT cana-3976 114 3 during during ADP cana-3976 114 4 the the DET cana-3976 114 5 subsequent subsequent ADJ cana-3976 114 6 visits visit NOUN cana-3976 114 7 , , PUNCT cana-3976 114 8 all all DET cana-3976 114 9 subjects subject NOUN cana-3976 114 10 were be AUX cana-3976 114 11 diagnosed diagnose VERB cana-3976 114 12 with with ADP cana-3976 114 13 dementia dementia NOUN cana-3976 114 14 . . PUNCT cana-3976 115 1 the the DET cana-3976 115 2 following follow VERB cana-3976 115 3 criteria criterion NOUN cana-3976 115 4 and and CCONJ cana-3976 115 5 indicators indicator NOUN cana-3976 115 6 are be AUX cana-3976 115 7 used use VERB cana-3976 115 8 in in ADP cana-3976 115 9 the the DET cana-3976 115 10 evaluation evaluation NOUN cana-3976 115 11 process process NOUN cana-3976 115 12 . . PUNCT cana-3976 116 1 data datum NOUN cana-3976 116 2 acquisition acquisition NOUN cana-3976 116 3 ( ( PUNCT cana-3976 116 4 datasets dataset NOUN cana-3976 116 5 ): ): PUNCT cana-3976 116 6 the the DET cana-3976 116 7 data datum NOUN cana-3976 116 8 comes come VERB cana-3976 116 9 from from ADP cana-3976 116 10 mri mri NOUN cana-3976 116 11 scans scan NOUN cana-3976 116 12 in in ADP cana-3976 116 13 the the DET cana-3976 116 14 oasis oasis NOUN cana-3976 116 15 dataset dataset NOUN cana-3976 116 16 , , PUNCT cana-3976 116 17 which which PRON cana-3976 116 18 may may AUX cana-3976 116 19 be be AUX cana-3976 116 20 found find VERB cana-3976 116 21 at at ADP cana-3976 116 22 https://www.oasisbrains.org https://www.oasisbrains.org NUM cana-3976 116 23 . . PUNCT cana-3976 117 1 the the DET cana-3976 117 2 open open ADJ cana-3976 117 3 access access NOUN cana-3976 117 4 to to ADP cana-3976 117 5 neuroimaging neuroimage VERB cana-3976 117 6 datasets dataset NOUN cana-3976 117 7 in in ADP cana-3976 117 8 science science NOUN cana-3976 117 9 ( ( PUNCT cana-3976 117 10 oasis oasis NOUN cana-3976 117 11 ) ) PUNCT cana-3976 117 12 initiative initiative NOUN cana-3976 117 13 intends intend VERB cana-3976 117 14 to to PART cana-3976 117 15 provide provide VERB cana-3976 117 16 scientific scientific ADJ cana-3976 117 17 researchers researcher NOUN cana-3976 117 18 with with ADP cana-3976 117 19 open open ADJ cana-3976 117 20 access access NOUN cana-3976 117 21 to to ADP cana-3976 117 22 brain brain NOUN cana-3976 117 23 neuroimaging neuroimage VERB cana-3976 117 24 datasets dataset NOUN cana-3976 117 25 [ [ X cana-3976 117 26 20 20 NUM cana-3976 117 27 ] ] PUNCT cana-3976 117 28 . . PUNCT cana-3976 118 1 collecting collect VERB cana-3976 118 2 and and CCONJ cana-3976 118 3 freely freely ADV cana-3976 118 4 disseminating disseminate VERB cana-3976 118 5 neuroimaging neuroimage VERB cana-3976 118 6 datasets dataset NOUN cana-3976 118 7 will will AUX cana-3976 118 8 enable enable VERB cana-3976 118 9 and and CCONJ cana-3976 118 10 aid aid VERB cana-3976 118 11 future future ADJ cana-3976 118 12 findings finding NOUN cana-3976 118 13 and and CCONJ cana-3976 118 14 clinical clinical ADJ cana-3976 118 15 neuroscience neuroscience NOUN cana-3976 118 16 like like ADP cana-3976 118 17 alzheimer alzheimer PROPN cana-3976 118 18 's 's PART cana-3976 118 19 disease disease NOUN cana-3976 118 20 neuroimaging neuroimaging NOUN cana-3976 118 21 initiative initiative NOUN cana-3976 118 22 ( ( PUNCT cana-3976 118 23 adni adni ADV cana-3976 118 24 ) ) PUNCT cana-3976 118 25 collect collect NOUN cana-3976 118 26 and and CCONJ cana-3976 118 27 disseminate disseminate VERB cana-3976 118 28 data datum NOUN cana-3976 118 29 . . PUNCT cana-3976 119 1 this this DET cana-3976 119 2 study study NOUN cana-3976 119 3 reported report VERB cana-3976 119 4 t1 t1 PROPN cana-3976 119 5 - - PUNCT cana-3976 119 6 weighted weight VERB cana-3976 119 7 mri mri NOUN cana-3976 119 8 data datum NOUN cana-3976 119 9 from from ADP cana-3976 119 10 oasis oasis NOUN cana-3976 119 11 participants participant NOUN cana-3976 119 12 who who PRON cana-3976 119 13 were be AUX cana-3976 119 14 either either ADV cana-3976 119 15 diagnosed diagnose VERB cana-3976 119 16 with with ADP cana-3976 119 17 alzheimer alzheimer PROPN cana-3976 119 18 's 's PART cana-3976 119 19 dementia dementia NOUN cana-3976 119 20 or or CCONJ cana-3976 119 21 did do AUX cana-3976 119 22 not not PART cana-3976 119 23 have have VERB cana-3976 119 24 the the DET cana-3976 119 25 disease disease NOUN cana-3976 119 26 . . PUNCT cana-3976 120 1 clinical clinical ADJ cana-3976 120 2 dementia dementia NOUN cana-3976 120 3 rating rating NOUN cana-3976 120 4 ( ( PUNCT cana-3976 120 5 cdr cdr PROPN cana-3976 120 6 ) ) PUNCT cana-3976 120 7 the the DET cana-3976 120 8 six six NUM cana-3976 120 9 domains domain NOUN cana-3976 120 10 of of ADP cana-3976 120 11 cognitive cognitive ADJ cana-3976 120 12 and and CCONJ cana-3976 120 13 functional functional ADJ cana-3976 120 14 performance performance NOUN cana-3976 120 15 associated associate VERB cana-3976 120 16 with with ADP cana-3976 120 17 alzheimer alzheimer PROPN cana-3976 120 18 's 's PART cana-3976 120 19 disease disease NOUN cana-3976 120 20 and and CCONJ cana-3976 120 21 other other ADJ cana-3976 120 22 dementias dementia NOUN cana-3976 120 23 include include VERB cana-3976 120 24 memory memory NOUN cana-3976 120 25 , , PUNCT cana-3976 120 26 orientation orientation NOUN cana-3976 120 27 , , PUNCT cana-3976 120 28 judgment judgment NOUN cana-3976 120 29 and and CCONJ cana-3976 120 30 problem problem NOUN cana-3976 120 31 - - PUNCT cana-3976 120 32 solving solving NOUN cana-3976 120 33 , , PUNCT cana-3976 120 34 home home NOUN cana-3976 120 35 and and CCONJ cana-3976 120 36 hobbies hobby NOUN cana-3976 120 37 , , PUNCT cana-3976 120 38 community community NOUN cana-3976 120 39 affairs affair NOUN cana-3976 120 40 , , PUNCT cana-3976 120 41 and and CCONJ cana-3976 120 42 personal personal ADJ cana-3976 120 43 care care NOUN cana-3976 120 44 . . PUNCT cana-3976 121 1 the the DET cana-3976 121 2 seventh seventh ADJ cana-3976 121 3 category category NOUN cana-3976 121 4 is be AUX cana-3976 121 5 personal personal ADJ cana-3976 121 6 care care NOUN cana-3976 121 7 . . PUNCT cana-3976 122 1 the the DET cana-3976 122 2 cdr cdr NOUN cana-3976 122 3 is be AUX cana-3976 122 4 a a DET cana-3976 122 5 five five NUM cana-3976 122 6 - - PUNCT cana-3976 122 7 point point NOUN cana-3976 122 8 scale scale NOUN cana-3976 122 9 used use VERB cana-3976 122 10 to to PART cana-3976 122 11 classify classify VERB cana-3976 122 12 these these DET cana-3976 122 13 various various ADJ cana-3976 122 14 groups group NOUN cana-3976 122 15 . . PUNCT cana-3976 123 1 a a DET cana-3976 123 2 semi semi ADJ cana-3976 123 3 - - ADJ cana-3976 123 4 structured structured ADJ cana-3976 123 5 interview interview NOUN cana-3976 123 6 with with ADP cana-3976 123 7 the the DET cana-3976 123 8 patient patient NOUN cana-3976 123 9 and and CCONJ cana-3976 123 10 a a DET cana-3976 123 11 credible credible ADJ cana-3976 123 12 informant informant NOUN cana-3976 123 13 or or CCONJ cana-3976 123 14 collateral collateral ADJ cana-3976 123 15 source source NOUN cana-3976 123 16 ( ( PUNCT cana-3976 123 17 for for ADP cana-3976 123 18 example example NOUN cana-3976 123 19 , , PUNCT cana-3976 123 20 a a DET cana-3976 123 21 member member NOUN cana-3976 123 22 of of ADP cana-3976 123 23 the the DET cana-3976 123 24 patient patient NOUN cana-3976 123 25 's 's PART cana-3976 123 26 family family NOUN cana-3976 123 27 ) ) PUNCT cana-3976 123 28 is be AUX cana-3976 123 29 used use VERB cana-3976 123 30 to to PART cana-3976 123 31 collect collect VERB cana-3976 123 32 the the DET cana-3976 123 33 information information NOUN cana-3976 123 34 needed need VERB cana-3976 123 35 to to PART cana-3976 123 36 generate generate VERB cana-3976 123 37 each each DET cana-3976 123 38 rating rating NOUN cana-3976 123 39 . . PUNCT cana-3976 124 1 table table NOUN cana-3976 124 2 1 1 NUM cana-3976 124 3 summarises summarise VERB cana-3976 124 4 the the DET cana-3976 124 5 findings finding NOUN cana-3976 124 6 of of ADP cana-3976 124 7 this this DET cana-3976 124 8 interview interview NOUN cana-3976 124 9 . . PUNCT cana-3976 125 1 table table NOUN cana-3976 125 2 1 1 NUM cana-3976 125 3 : : PUNCT cana-3976 125 4 clinical clinical ADJ cana-3976 125 5 dementia dementia NOUN cana-3976 125 6 rating rating NOUN cana-3976 125 7 score score NOUN cana-3976 125 8 description description NOUN cana-3976 125 9 0 0 NUM cana-3976 125 10 normal normal ADJ cana-3976 125 11 0.5 0.5 NUM cana-3976 125 12 very very ADV cana-3976 125 13 mild mild ADJ cana-3976 125 14 dementia dementia NOUN cana-3976 125 15 1 1 NUM cana-3976 125 16 mild mild ADJ cana-3976 125 17 dementia dementia NOUN cana-3976 125 18 2 2 NUM cana-3976 125 19 moderate moderate ADJ cana-3976 125 20 dementia dementia NOUN cana-3976 125 21 3 3 NUM cana-3976 125 22 severe severe ADJ cana-3976 125 23 dementia dementia NOUN cana-3976 125 24 the the DET cana-3976 125 25 cdr cdr PROPN cana-3976 125 26 table table NOUN cana-3976 125 27 's 's PART cana-3976 125 28 descriptive descriptive ADJ cana-3976 125 29 anchors anchor NOUN cana-3976 125 30 help help VERB cana-3976 125 31 the the DET cana-3976 125 32 physician physician NOUN cana-3976 125 33 to to PART cana-3976 125 34 assign assign VERB cana-3976 125 35 appropriate appropriate ADJ cana-3976 125 36 ratings rating NOUN cana-3976 125 37 based base VERB cana-3976 125 38 on on ADP cana-3976 125 39 interview interview NOUN cana-3976 125 40 data datum NOUN cana-3976 125 41 and and CCONJ cana-3976 125 42 clinical clinical ADJ cana-3976 125 43 judgment judgment NOUN cana-3976 125 44 . . PUNCT cana-3976 126 1 a a DET cana-3976 126 2 method method NOUN cana-3976 126 3 can can AUX cana-3976 126 4 generate generate VERB cana-3976 126 5 an an DET cana-3976 126 6 overall overall ADJ cana-3976 126 7 cdr cdr NOUN cana-3976 126 8 score score NOUN cana-3976 126 9 and and CCONJ cana-3976 126 10 scores score NOUN cana-3976 126 11 for for ADP cana-3976 126 12 each each DET cana-3976 126 13 domain domain NOUN cana-3976 126 14 . . PUNCT cana-3976 127 1 this this DET cana-3976 127 2 score score NOUN cana-3976 127 3 is be AUX cana-3976 127 4 vital vital ADJ cana-3976 127 5 for for ADP cana-3976 127 6 characterizing characterize VERB cana-3976 127 7 and and CCONJ cana-3976 127 8 tracking track VERB cana-3976 127 9 a a DET cana-3976 127 10 patient patient NOUN cana-3976 127 11 's 's PART cana-3976 127 12 level level NOUN cana-3976 127 13 of of ADP cana-3976 127 14 impairment impairment NOUN cana-3976 127 15 and and CCONJ cana-3976 127 16 dementia dementia NOUN cana-3976 127 17 as as SCONJ cana-3976 127 18 follows follow VERB cana-3976 127 19 : : PUNCT cana-3976 127 20 furthermore furthermore ADV cana-3976 127 21 , , PUNCT cana-3976 127 22 the the DET cana-3976 127 23 oasis-1 oasis-1 NUM cana-3976 127 24 dataset dataset NOUN cana-3976 127 25 had have VERB cana-3976 127 26 predictor predictor NOUN cana-3976 127 27 variables variable NOUN cana-3976 127 28 types type NOUN cana-3976 127 29 that that PRON cana-3976 127 30 will will AUX cana-3976 127 31 be be AUX cana-3976 127 32 defined define VERB cana-3976 127 33 in in ADP cana-3976 127 34 the the DET cana-3976 127 35 following follow VERB cana-3976 127 36 sections section NOUN cana-3976 127 37 . . PUNCT cana-3976 128 1 communications communication NOUN cana-3976 128 2 on on ADP cana-3976 128 3 applied apply VERB cana-3976 128 4 nonlinear nonlinear ADJ cana-3976 128 5 analysis analysis NOUN cana-3976 128 6 issn issn NOUN cana-3976 128 7 : : PUNCT cana-3976 128 8 1074 1074 NUM cana-3976 128 9 - - PUNCT cana-3976 128 10 133x 133x NUM cana-3976 128 11 vol vol NOUN cana-3976 128 12 32 32 NUM cana-3976 128 13 no no NOUN cana-3976 128 14 . . PUNCT cana-3976 129 1 9s 9s NUM cana-3976 129 2 ( ( PUNCT cana-3976 129 3 2025 2025 NUM cana-3976 129 4 ) ) PUNCT cana-3976 130 1 707 707 NUM cana-3976 130 2 https://internationalpubls.com https://internationalpubls.com X cana-3976 130 3 socio socio NOUN cana-3976 130 4 - - ADJ cana-3976 130 5 demographic demographic ADJ cana-3976 130 6 predictor predictor NOUN cana-3976 130 7 variables variable NOUN cana-3976 130 8 numerous numerous ADJ cana-3976 130 9 oasis-1 oasis-1 NUM cana-3976 130 10 dataset dataset ADJ cana-3976 130 11 variables variable NOUN cana-3976 130 12 provided provide VERB cana-3976 130 13 patient patient ADJ cana-3976 130 14 sociodemographic sociodemographic ADJ cana-3976 130 15 data datum NOUN cana-3976 130 16 . . PUNCT cana-3976 131 1 they they PRON cana-3976 131 2 list list VERB cana-3976 131 3 the the DET cana-3976 131 4 variables variable NOUN cana-3976 131 5 in in ADP cana-3976 131 6 table table NOUN cana-3976 131 7 2 2 NUM cana-3976 131 8 below below ADV cana-3976 131 9 . . PUNCT cana-3976 132 1 table table NOUN cana-3976 132 2 2 2 NUM cana-3976 132 3 : : PUNCT cana-3976 132 4 socio socio NOUN cana-3976 132 5 - - ADJ cana-3976 132 6 demographic demographic ADJ cana-3976 132 7 predictor predictor NOUN cana-3976 132 8 variables variable VERB cana-3976 132 9 variable variable ADJ cana-3976 132 10 value value NOUN cana-3976 132 11 description description NOUN cana-3976 132 12 gender gender NOUN cana-3976 132 13 0 0 NUM cana-3976 132 14 female female ADJ cana-3976 132 15 1 1 NUM cana-3976 132 16 male male NOUN cana-3976 132 17 age age NOUN cana-3976 132 18 ( ( PUNCT cana-3976 132 19 18 18 NUM cana-3976 132 20 , , PUNCT cana-3976 132 21 96 96 NUM cana-3976 132 22 ) ) PUNCT cana-3976 132 23 education education NOUN cana-3976 132 24 1 1 NUM cana-3976 132 25 high high ADJ cana-3976 132 26 school school NOUN cana-3976 132 27 2 2 NUM cana-3976 132 28 hs hs NOUN cana-3976 132 29 graduate graduate VERB cana-3976 132 30 3 3 NUM cana-3976 132 31 some some DET cana-3976 132 32 college college NOUN cana-3976 132 33 4 4 NUM cana-3976 132 34 college college NOUN cana-3976 132 35 graduate graduate NOUN cana-3976 132 36 5 5 NUM cana-3976 132 37 beyond beyond ADP cana-3976 132 38 college college NOUN cana-3976 132 39 socioeconomic socioeconomic ADJ cana-3976 132 40 status status NOUN cana-3976 132 41 ( ( PUNCT cana-3976 132 42 ses ses PROPN cana-3976 132 43 ) ) PUNCT cana-3976 132 44 1 1 NUM cana-3976 132 45 lower low ADJ cana-3976 132 46 2 2 NUM cana-3976 132 47 lower lower ADV cana-3976 132 48 middle middle NOUN cana-3976 132 49 3 3 NUM cana-3976 132 50 middle middle NOUN cana-3976 132 51 4 4 NUM cana-3976 132 52 upper upper ADJ cana-3976 132 53 middle middle NOUN cana-3976 132 54 5 5 NUM cana-3976 132 55 upper upper ADJ cana-3976 132 56 the the DET cana-3976 132 57 cdr cdr PROPN cana-3976 132 58 table table NOUN cana-3976 132 59 's 's PART cana-3976 132 60 descriptive descriptive ADJ cana-3976 132 61 anchors anchor NOUN cana-3976 132 62 help help VERB cana-3976 132 63 the the DET cana-3976 132 64 attending attend VERB cana-3976 132 65 physician physician NOUN cana-3976 132 66 to to PART cana-3976 132 67 allocate allocate VERB cana-3976 132 68 appropriate appropriate ADJ cana-3976 132 69 grades grade NOUN cana-3976 132 70 with with ADP cana-3976 132 71 consultation consultation NOUN cana-3976 132 72 statistics statistic NOUN cana-3976 132 73 and and CCONJ cana-3976 132 74 medical medical ADJ cana-3976 132 75 judgment judgment NOUN cana-3976 132 76 . . PUNCT cana-3976 133 1 there there PRON cana-3976 133 2 is be VERB cana-3976 133 3 a a DET cana-3976 133 4 method method NOUN cana-3976 133 5 for for ADP cana-3976 133 6 determining determine VERB cana-3976 133 7 the the DET cana-3976 133 8 total total ADJ cana-3976 133 9 score score NOUN cana-3976 133 10 of of ADP cana-3976 133 11 the the DET cana-3976 133 12 cdr cdr NOUN cana-3976 133 13 in in ADP cana-3976 133 14 addition addition NOUN cana-3976 133 15 to to ADP cana-3976 133 16 the the DET cana-3976 133 17 ratings rating NOUN cana-3976 133 18 for for ADP cana-3976 133 19 each each DET cana-3976 133 20 domain domain NOUN cana-3976 133 21 . . PUNCT cana-3976 134 1 in in ADP cana-3976 134 2 the the DET cana-3976 134 3 following following ADJ cana-3976 134 4 ways way NOUN cana-3976 134 5 , , PUNCT cana-3976 134 6 this this DET cana-3976 134 7 score score NOUN cana-3976 134 8 can can AUX cana-3976 134 9 be be AUX cana-3976 134 10 used use VERB cana-3976 134 11 to to PART cana-3976 134 12 characterize characterize VERB cana-3976 134 13 and and CCONJ cana-3976 134 14 record record VERB cana-3976 134 15 a a DET cana-3976 134 16 patient patient NOUN cana-3976 134 17 's 's PART cana-3976 134 18 level level NOUN cana-3976 134 19 of of ADP cana-3976 134 20 impairment impairment NOUN cana-3976 134 21 and and CCONJ cana-3976 134 22 dementia dementia NOUN cana-3976 134 23 : : PUNCT cana-3976 134 24 the the DET cana-3976 134 25 oasis-1 oasis-1 NUM cana-3976 134 26 dataset dataset NOUN cana-3976 134 27 had have VERB cana-3976 134 28 three three NUM cana-3976 134 29 categories category NOUN cana-3976 134 30 of of ADP cana-3976 134 31 predictor predictor NOUN cana-3976 134 32 variables variable NOUN cana-3976 134 33 : : PUNCT cana-3976 134 34 demographic demographic ADJ cana-3976 134 35 , , PUNCT cana-3976 134 36 clinical clinical ADJ cana-3976 134 37 , , PUNCT cana-3976 134 38 and and CCONJ cana-3976 134 39 imaging imaging NOUN cana-3976 134 40 predictor predictor NOUN cana-3976 134 41 variables variable NOUN cana-3976 134 42 . . PUNCT cana-3976 135 1 in in ADP cana-3976 135 2 the the DET cana-3976 135 3 following follow VERB cana-3976 135 4 paragraphs paragraph NOUN cana-3976 135 5 , , PUNCT cana-3976 135 6 definitions definition NOUN cana-3976 135 7 for for ADP cana-3976 135 8 each each PRON cana-3976 135 9 of of ADP cana-3976 135 10 these these DET cana-3976 135 11 variable variable ADJ cana-3976 135 12 categories category NOUN cana-3976 135 13 will will AUX cana-3976 135 14 be be AUX cana-3976 135 15 presented present VERB cana-3976 135 16 . . PUNCT cana-3976 136 1 clinical clinical ADJ cana-3976 136 2 predictor predictor NOUN cana-3976 136 3 variables variable NOUN cana-3976 136 4 , , PUNCT cana-3976 136 5 non non ADJ cana-3976 136 6 - - ADJ cana-3976 136 7 imagery imagery ADJ cana-3976 136 8 data datum NOUN cana-3976 136 9 : : PUNCT cana-3976 136 10 we we PRON cana-3976 136 11 could could AUX cana-3976 136 12 also also ADV cana-3976 136 13 employ employ VERB cana-3976 136 14 other other ADJ cana-3976 136 15 clinical clinical ADJ cana-3976 136 16 prognostic prognostic ADJ cana-3976 136 17 markers marker NOUN cana-3976 136 18 that that PRON cana-3976 136 19 did do AUX cana-3976 136 20 not not PART cana-3976 136 21 entail entail VERB cana-3976 136 22 imagery imagery NOUN cana-3976 136 23 omitted omit VERB cana-3976 136 24 from from ADP cana-3976 136 25 the the DET cana-3976 136 26 model model NOUN cana-3976 136 27 since since SCONJ cana-3976 136 28 three three NUM cana-3976 136 29 of of ADP cana-3976 136 30 the the DET cana-3976 136 31 four four NUM cana-3976 136 32 variables variable NOUN cana-3976 136 33 ( ( PUNCT cana-3976 136 34 excluding exclude VERB cana-3976 136 35 the the DET cana-3976 136 36 mmse mmse ADJ cana-3976 136 37 ) ) PUNCT cana-3976 136 38 required require VERB cana-3976 136 39 imagery imagery NOUN cana-3976 136 40 . . PUNCT cana-3976 137 1 the the DET cana-3976 137 2 definitions definition NOUN cana-3976 137 3 for for ADP cana-3976 137 4 these these DET cana-3976 137 5 variables variable NOUN cana-3976 137 6 will will AUX cana-3976 137 7 be be AUX cana-3976 137 8 supplied supply VERB cana-3976 137 9 in in ADP cana-3976 137 10 the the DET cana-3976 137 11 following follow VERB cana-3976 137 12 text text NOUN cana-3976 137 13 . . PUNCT cana-3976 138 1 minimental minimental ADJ cana-3976 138 2 state state NOUN cana-3976 138 3 examination examination NOUN cana-3976 138 4 ( ( PUNCT cana-3976 138 5 mmse mmse ADJ cana-3976 138 6 ) ) PUNCT cana-3976 138 7 . . PUNCT cana-3976 139 1 this this PRON cana-3976 139 2 contains contain VERB cana-3976 139 3 a a DET cana-3976 139 4 thirty thirty NUM cana-3976 139 5 - - PUNCT cana-3976 139 6 question question NOUN cana-3976 139 7 examination examination NOUN cana-3976 139 8 that that PRON cana-3976 139 9 is be AUX cana-3976 139 10 useful useful ADJ cana-3976 139 11 and and CCONJ cana-3976 139 12 reliable reliable ADJ cana-3976 139 13 for for ADP cana-3976 139 14 dementia dementia NOUN cana-3976 139 15 diagnosis diagnosis NOUN cana-3976 139 16 [ [ X cana-3976 139 17 21 21 NUM cana-3976 139 18 ] ] PUNCT cana-3976 139 19 . . PUNCT cana-3976 140 1 we we PRON cana-3976 140 2 completed complete VERB cana-3976 140 3 the the DET cana-3976 140 4 variables variable NOUN cana-3976 140 5 at at ADP cana-3976 140 6 a a DET cana-3976 140 7 rate rate NOUN cana-3976 140 8 of of ADP cana-3976 140 9 56 56 NUM cana-3976 140 10 % % NOUN cana-3976 140 11 ( ( PUNCT cana-3976 140 12 235 235 NUM cana-3976 140 13 out out ADP cana-3976 140 14 of of ADP cana-3976 140 15 communications communication NOUN cana-3976 140 16 on on ADP cana-3976 140 17 applied apply VERB cana-3976 140 18 nonlinear nonlinear ADJ cana-3976 140 19 analysis analysis NOUN cana-3976 140 20 issn issn NOUN cana-3976 140 21 : : PUNCT cana-3976 140 22 1074 1074 NUM cana-3976 140 23 - - PUNCT cana-3976 140 24 133x 133x NUM cana-3976 140 25 vol vol NOUN cana-3976 140 26 32 32 NUM cana-3976 140 27 no no NOUN cana-3976 140 28 . . PUNCT cana-3976 141 1 9s 9s NUM cana-3976 141 2 ( ( PUNCT cana-3976 141 3 2025 2025 NUM cana-3976 141 4 ) ) PUNCT cana-3976 141 5 708 708 NUM cana-3976 141 6 https://internationalpubls.com https://internationalpubls.com X cana-3976 141 7 416 416 NUM cana-3976 141 8 ) ) PUNCT cana-3976 141 9 . . PUNCT cana-3976 142 1 the the DET cana-3976 142 2 median median NOUN cana-3976 142 3 was be AUX cana-3976 142 4 used use VERB cana-3976 142 5 to to PART cana-3976 142 6 fill fill VERB cana-3976 142 7 in in ADP cana-3976 142 8 the the DET cana-3976 142 9 missing miss VERB cana-3976 142 10 values value NOUN cana-3976 142 11 in in ADP cana-3976 142 12 the the DET cana-3976 142 13 data datum NOUN cana-3976 142 14 . . PUNCT cana-3976 143 1 it it PRON cana-3976 143 2 included include VERB cana-3976 143 3 the the DET cana-3976 143 4 mmse mmse NOUN cana-3976 143 5 in in ADP cana-3976 143 6 a a DET cana-3976 143 7 model model NOUN cana-3976 143 8 that that PRON cana-3976 143 9 did do AUX cana-3976 143 10 not not PART cana-3976 143 11 consider consider VERB cana-3976 143 12 imaging imaging NOUN cana-3976 143 13 . . PUNCT cana-3976 144 1 atlas atlas PROPN cana-3976 144 2 scaling scale VERB cana-3976 144 3 factor factor NOUN cana-3976 144 4 ( ( PUNCT cana-3976 144 5 asf asf NOUN cana-3976 144 6 ): ): PUNCT cana-3976 144 7 ( ( PUNCT cana-3976 144 8 0.88โ€“1.56 0.88โ€“1.56 NUM cana-3976 144 9 ) ) PUNCT cana-3976 144 10 ( ( PUNCT cana-3976 144 11 observed observe VERB cana-3976 144 12 ) ) PUNCT cana-3976 144 13 . . PUNCT cana-3976 145 1 this this DET cana-3976 145 2 scaling scale VERB cana-3976 145 3 feature feature NOUN cana-3976 145 4 is be AUX cana-3976 145 5 used use VERB cana-3976 145 6 to to PART cana-3976 145 7 assess assess VERB cana-3976 145 8 estimated estimate VERB cana-3976 145 9 total total ADJ cana-3976 145 10 intracranial intracranial ADJ cana-3976 145 11 volume volume NOUN cana-3976 145 12 ( ( PUNCT cana-3976 145 13 etiv etiv NOUN cana-3976 145 14 ) ) PUNCT cana-3976 145 15 data datum NOUN cana-3976 146 1 [ [ X cana-3976 146 2 22 22 NUM cana-3976 146 3 ] ] PUNCT cana-3976 146 4 . . PUNCT cana-3976 147 1 estimated estimate VERB cana-3976 147 2 total total ADJ cana-3976 147 3 intracranial intracranial ADJ cana-3976 147 4 volume volume NOUN cana-3976 147 5 ( ( PUNCT cana-3976 147 6 etiv etiv PROPN cana-3976 147 7 ): ): PUNCT cana-3976 147 8 ( ( PUNCT cana-3976 147 9 1132โ€“1992 1132โ€“1992 NUM cana-3976 147 10 ) ) PUNCT cana-3976 147 11 mm3 mm3 NOUN cana-3976 148 1 [ [ X cana-3976 148 2 23 23 NUM cana-3976 148 3 ] ] PUNCT cana-3976 148 4 . . PUNCT cana-3976 149 1 this this PRON cana-3976 149 2 calculates calculate VERB cana-3976 149 3 the the DET cana-3976 149 4 volume volume NOUN cana-3976 149 5 of of ADP cana-3976 149 6 the the DET cana-3976 149 7 brain brain NOUN cana-3976 149 8 contained contain VERB cana-3976 149 9 within within ADP cana-3976 149 10 the the DET cana-3976 149 11 skull skull NOUN cana-3976 149 12 . . PUNCT cana-3976 150 1 this this DET cana-3976 150 2 variable variable NOUN cana-3976 150 3 was be AUX cana-3976 150 4 complete complete ADJ cana-3976 150 5 to to ADP cana-3976 150 6 the the DET cana-3976 150 7 letter letter NOUN cana-3976 150 8 ( ( PUNCT cana-3976 150 9 416 416 NUM cana-3976 150 10 out out ADP cana-3976 150 11 of of ADP cana-3976 150 12 416 416 NUM cana-3976 150 13 ) ) PUNCT cana-3976 150 14 . . PUNCT cana-3976 151 1 normalized normalize VERB cana-3976 151 2 whole whole ADJ cana-3976 151 3 brain brain NOUN cana-3976 151 4 volume volume NOUN cana-3976 151 5 ( ( PUNCT cana-3976 151 6 nwbv nwbv PROPN cana-3976 151 7 ): ): PUNCT cana-3976 151 8 ( ( PUNCT cana-3976 151 9 0.64โ€“0.90 0.64โ€“0.90 NUM cana-3976 151 10 ) ) PUNCT cana-3976 152 1 mg mg PROPN cana-3976 152 2 ( ( PUNCT cana-3976 152 3 observed observe VERB cana-3976 152 4 ) ) PUNCT cana-3976 152 5 . . PUNCT cana-3976 153 1 this this PRON cana-3976 153 2 delivers deliver VERB cana-3976 153 3 brain brain NOUN cana-3976 153 4 volume volume NOUN cana-3976 153 5 estimation estimation NOUN cana-3976 153 6 . . PUNCT cana-3976 154 1 preprocessing preprocesse VERB cana-3976 154 2 step step NOUN cana-3976 154 3 : : PUNCT cana-3976 154 4 the the DET cana-3976 154 5 classifications classification NOUN cana-3976 154 6 in in ADP cana-3976 154 7 the the DET cana-3976 154 8 obtained obtain VERB cana-3976 154 9 dataset dataset NOUN cana-3976 154 10 are be AUX cana-3976 154 11 not not PART cana-3976 154 12 evenly evenly ADV cana-3976 154 13 distributed distribute VERB cana-3976 154 14 . . PUNCT cana-3976 155 1 to to PART cana-3976 155 2 circumvent circumvent VERB cana-3976 155 3 this this DET cana-3976 155 4 issue issue NOUN cana-3976 155 5 , , PUNCT cana-3976 155 6 we we PRON cana-3976 155 7 resample resample VERB cana-3976 155 8 using use VERB cana-3976 155 9 two two NUM cana-3976 155 10 sampling sample VERB cana-3976 155 11 approaches approach NOUN cana-3976 155 12 . . PUNCT cana-3976 156 1 undersampling undersample VERB cana-3976 156 2 is be AUX cana-3976 156 3 the the DET cana-3976 156 4 removal removal NOUN cana-3976 156 5 of of ADP cana-3976 156 6 examples example NOUN cana-3976 156 7 from from ADP cana-3976 156 8 an an DET cana-3976 156 9 overrepresented overrepresented ADJ cana-3976 156 10 class class NOUN cana-3976 156 11 , , PUNCT cana-3976 156 12 whereas whereas SCONJ cana-3976 156 13 oversampling oversampling NOUN cana-3976 156 14 is be AUX cana-3976 156 15 the the DET cana-3976 156 16 addition addition NOUN cana-3976 156 17 of of ADP cana-3976 156 18 more more ADJ cana-3976 156 19 cases case NOUN cana-3976 156 20 to to ADP cana-3976 156 21 an an DET cana-3976 156 22 already already ADV cana-3976 156 23 adequately adequately ADV cana-3976 156 24 represented represent VERB cana-3976 156 25 class class NOUN cana-3976 156 26 . . PUNCT cana-3976 157 1 local local ADJ cana-3976 157 2 imbalance imbalance NOUN cana-3976 157 3 and and CCONJ cana-3976 157 4 spatial spatial ADJ cana-3976 157 5 sparsity sparsity NOUN cana-3976 157 6 are be AUX cana-3976 157 7 two two NUM cana-3976 157 8 characteristics characteristic NOUN cana-3976 157 9 associated associate VERB cana-3976 157 10 with with ADP cana-3976 157 11 sample sample NOUN cana-3976 157 12 distribution distribution NOUN cana-3976 157 13 at at ADP cana-3976 157 14 the the DET cana-3976 157 15 neighbourhood neighbourhood NOUN cana-3976 157 16 level level NOUN cana-3976 157 17 . . PUNCT cana-3976 158 1 taking take VERB cana-3976 158 2 these these DET cana-3976 158 3 two two NUM cana-3976 158 4 aspects aspect NOUN cana-3976 158 5 into into ADP cana-3976 158 6 consideration consideration NOUN cana-3976 158 7 , , PUNCT cana-3976 158 8 the the DET cana-3976 158 9 hvdm hvdm PROPN cana-3976 158 10 distance distance NOUN cana-3976 158 11 incorporates incorporate VERB cana-3976 158 12 the the DET cana-3976 158 13 weight weight NOUN cana-3976 158 14 constants constant NOUN cana-3976 158 15 : : PUNCT cana-3976 158 16 ๐‘‘๐‘Š ๐‘‘๐‘Š PROPN cana-3976 158 17 ๐ผ๐‘…,๐‘š(๐‘ฅ1 ๐ผ๐‘…,๐‘š(๐‘ฅ1 PROPN cana-3976 158 18 , , PUNCT cana-3976 158 19 ๐‘ฅ2 ๐‘ฅ2 NOUN cana-3976 158 20 ) ) PUNCT cana-3976 158 21 = = PRON cana-3976 158 22 { { PUNCT cana-3976 158 23 ๐‘’(๐ผ๐‘…+ ๐‘’(๐ผ๐‘…+ NOUN cana-3976 158 24 ) ) PUNCT cana-3976 158 25 ๐‘š ๐‘š NOUN cana-3976 158 26 . . PUNCT cana-3976 159 1 ๐‘‘๐ป๐‘‰๐ท๐‘€(๐‘ฅ1 ๐‘‘๐ป๐‘‰๐ท๐‘€(๐‘ฅ1 NOUN cana-3976 159 2 , , PUNCT cana-3976 159 3 ๐‘ฅ2 ๐‘ฅ2 NOUN cana-3976 159 4 ) ) PUNCT cana-3976 159 5 , , PUNCT cana-3976 159 6 ๐‘–๐‘“ ๐‘–๐‘“ NUM cana-3976 159 7 ๐‘ฅ2 ๐‘ฅ2 NOUN cana-3976 159 8 ๐‘–๐‘  ๐‘–๐‘  NOUN cana-3976 159 9 ๐‘๐‘œ๐‘ ๐‘–๐‘ก๐‘–๐‘ฃ๐‘’ ๐‘๐‘œ๐‘ ๐‘–๐‘ก๐‘–๐‘ฃ๐‘’ NOUN cana-3976 159 10 ๐‘’(๐ผ๐‘…โˆ’)๐‘š ๐‘’(๐ผ๐‘…โˆ’)๐‘š NOUN cana-3976 159 11 . . PUNCT cana-3976 160 1 ๐‘‘๐ป๐‘‰๐ท๐‘€(๐‘ฅ1 ๐‘‘๐ป๐‘‰๐ท๐‘€(๐‘ฅ1 NOUN cana-3976 160 2 , , PUNCT cana-3976 160 3 ๐‘ฅ2 ๐‘ฅ2 NOUN cana-3976 160 4 ) ) PUNCT cana-3976 160 5 , , PUNCT cana-3976 160 6 ๐‘–๐‘“ ๐‘–๐‘“ NUM cana-3976 160 7 ๐‘ฅ2 ๐‘ฅ2 NOUN cana-3976 160 8 ๐‘–๐‘  ๐‘–๐‘  CCONJ cana-3976 160 9 ๐‘›๐‘’๐‘”๐‘Ž๐‘ก๐‘–๐‘ฃ๐‘’ ๐‘›๐‘’๐‘”๐‘Ž๐‘ก๐‘–๐‘ฃ๐‘’ PROPN cana-3976 160 10 ( ( PUNCT cana-3976 160 11 1 1 NUM cana-3976 160 12 ) ) PUNCT cana-3976 160 13 where where SCONJ cana-3976 160 14 x1denotes x1denote NOUN cana-3976 160 15 seed seed NOUN cana-3976 160 16 and and CCONJ cana-3976 160 17 x2 x2 PROPN cana-3976 160 18 denotes denote NOUN cana-3976 160 19 candidate candidate NOUN cana-3976 160 20 for for ADP cana-3976 160 21 the the DET cana-3976 160 22 closest close ADJ cana-3976 160 23 neighbour neighbour NOUN cana-3976 160 24 . . PUNCT cana-3976 161 1 the the DET cana-3976 161 2 imbalance imbalance NOUN cana-3976 161 3 ratio ratio NOUN cana-3976 161 4 , , PUNCT cana-3976 161 5 abbreviated abbreviate VERB cana-3976 161 6 as as ADP cana-3976 161 7 ir ir PROPN cana-3976 161 8 . . PROPN cana-3976 161 9 similarly similarly ADV cana-3976 161 10 , , PUNCT cana-3976 161 11 the the DET cana-3976 161 12 weight weight NOUN cana-3976 161 13 constants constant NOUN cana-3976 161 14 are be AUX cana-3976 161 15 signified signify VERB cana-3976 161 16 by by ADP cana-3976 161 17 the the DET cana-3976 161 18 symbols symbol NOUN cana-3976 161 19 f+ f+ PROPN cana-3976 161 20 and and CCONJ cana-3976 161 21 f- f- NUM cana-3976 161 22 : : PUNCT cana-3976 161 23 ๐’‡+(๐ผ๐‘… ๐’‡+(๐ผ๐‘… NOUN cana-3976 161 24 , , PUNCT cana-3976 161 25 ๐‘š ๐‘š NOUN cana-3976 161 26 ) ) PUNCT cana-3976 161 27 = = SYM cana-3976 162 1 ๐‘’(๐ผ๐‘…+ ๐‘’(๐ผ๐‘…+ NOUN cana-3976 162 2 ) ) PUNCT cana-3976 162 3 ๐‘š ๐‘š NOUN cana-3976 162 4 , , PUNCT cana-3976 162 5 ( ( PUNCT cana-3976 162 6 2 2 X cana-3976 162 7 ) ) PUNCT cana-3976 162 8 ๐’‡โˆ’(๐ผ๐‘… ๐’‡โˆ’(๐ผ๐‘… NOUN cana-3976 162 9 , , PUNCT cana-3976 162 10 ๐‘š ๐‘š NOUN cana-3976 162 11 ) ) PUNCT cana-3976 162 12 = = SYM cana-3976 162 13 ๐‘’(๐ผ๐‘…โˆ’)๐‘š ๐‘’(๐ผ๐‘…โˆ’)๐‘š NOUN cana-3976 162 14 , , PUNCT cana-3976 162 15 ( ( PUNCT cana-3976 162 16 3 3 X cana-3976 162 17 ) ) PUNCT cana-3976 162 18 local local ADJ cana-3976 162 19 imbalance imbalance NOUN cana-3976 162 20 : : PUNCT cana-3976 162 21 a a DET cana-3976 162 22 global global ADJ cana-3976 162 23 imbalance imbalance NOUN cana-3976 162 24 ratio ratio NOUN cana-3976 162 25 , , PUNCT cana-3976 162 26 represented represent VERB cana-3976 162 27 by by ADP cana-3976 162 28 ir ir PROPN cana-3976 162 29 , , PUNCT cana-3976 162 30 gives give VERB cana-3976 162 31 a a DET cana-3976 162 32 rough rough ADJ cana-3976 162 33 depiction depiction NOUN cana-3976 162 34 of of ADP cana-3976 162 35 the the DET cana-3976 162 36 degree degree NOUN cana-3976 162 37 of of ADP cana-3976 162 38 local local ADJ cana-3976 162 39 imbalance imbalance NOUN cana-3976 162 40 . . PUNCT cana-3976 163 1 when when SCONJ cana-3976 163 2 the the DET cana-3976 163 3 quantity quantity NOUN cana-3976 163 4 of of ADP cana-3976 163 5 characteristics characteristic NOUN cana-3976 163 6 m m VERB cana-3976 163 7 is be AUX cana-3976 163 8 held hold VERB cana-3976 163 9 constant constant ADJ cana-3976 163 10 , , PUNCT cana-3976 163 11 the the DET cana-3976 163 12 weight weight NOUN cana-3976 163 13 constantsfulfil constantsfulfil NOUN cana-3976 163 14 the the DET cana-3976 163 15 aforementioned aforementioned ADJ cana-3976 163 16 criteria criterion NOUN cana-3976 163 17 since since SCONJ cana-3976 163 18 ir+ ir+ PROPN cana-3976 163 19 > > X cana-3976 163 20 ir ir PROPN cana-3976 163 21 and and CCONJ cana-3976 163 22 the the DET cana-3976 163 23 exponential exponential ADJ cana-3976 163 24 function function NOUN cana-3976 163 25 expands expand VERB cana-3976 163 26 in in ADP cana-3976 163 27 a a DET cana-3976 163 28 steady steady ADJ cana-3976 163 29 manner manner NOUN cana-3976 163 30 . . PUNCT cana-3976 164 1 ๐’‡+(๐ผ๐‘… ๐’‡+(๐ผ๐‘… NOUN cana-3976 164 2 , , PUNCT cana-3976 164 3 ๐‘š ๐‘š NOUN cana-3976 164 4 ) ) PUNCT cana-3976 164 5 < < X cana-3976 164 6 ๐’‡โˆ’(๐ผ๐‘… ๐’‡โˆ’(๐ผ๐‘… PROPN cana-3976 164 7 , , PUNCT cana-3976 164 8 ๐‘š ๐‘š NOUN cana-3976 164 9 ) ) PUNCT cana-3976 164 10 algorithm algorithm NOUN cana-3976 164 11 1 1 NUM cana-3976 164 12 : : PUNCT cana-3976 164 13 smote smote ADJ cana-3976 164 14 - - PUNCT cana-3976 164 15 wenn wenn VERB cana-3976 164 16 input input NOUN cana-3976 164 17 : : PUNCT cana-3976 164 18 tr tr VERB cana-3976 164 19 , , PUNCT cana-3976 164 20 the the DET cana-3976 164 21 training training NOUN cana-3976 164 22 set set NOUN cana-3976 164 23 ; ; PUNCT cana-3976 164 24 p p X cana-3976 164 25 , , PUNCT cana-3976 164 26 the the DET cana-3976 164 27 nearest near ADJ cana-3976 164 28 neighbors neighbor NOUN cana-3976 164 29 in in ADP cana-3976 164 30 smote smote ADJ cana-3976 164 31 ; ; PUNCT cana-3976 164 32 k k X cana-3976 164 33 , , PUNCT cana-3976 164 34 the the DET cana-3976 164 35 no no NOUN cana-3976 164 36 . . PUNCT cana-3976 164 37 of of ADP cana-3976 164 38 nearest near ADJ cana-3976 164 39 neighbors neighbor NOUN cana-3976 164 40 in in ADP cana-3976 164 41 data datum NOUN cana-3976 164 42 cleaning cleaning NOUN cana-3976 164 43 methods method NOUN cana-3976 164 44 . . PUNCT cana-3976 165 1 output output NOUN cana-3976 165 2 : : PUNCT cana-3976 165 3 new_tr new_tr ADV cana-3976 165 4 , , PUNCT cana-3976 165 5 the the DET cana-3976 165 6 training training NOUN cana-3976 165 7 setafter setafter NOUN cana-3976 165 8 using use VERB cana-3976 165 9 smote smote NOUN cana-3976 165 10 - - PUNCT cana-3976 165 11 wenn wenn VERB cana-3976 165 12 divide divide NOUN cana-3976 165 13 into into ADP cana-3976 165 14 positive positive ADJ cana-3976 165 15 and and CCONJ cana-3976 165 16 negative negative ADJ cana-3976 165 17 subsets subset NOUN cana-3976 165 18 ; ; PUNCT cana-3976 165 19 ๐‘‡๐‘Ÿ ๐‘‡๐‘Ÿ PROPN cana-3976 165 20 = = SYM cana-3976 165 21 ๐‘ƒ๐‘œ๐‘  ๐‘ƒ๐‘œ๐‘  PROPN cana-3976 165 22 โ‹ƒ โ‹ƒ PROPN cana-3976 165 23 ๐‘๐‘’๐‘” ๐‘๐‘’๐‘” PROPN cana-3976 165 24 ; ; PUNCT cana-3976 165 25 oversample oversample NOUN cana-3976 165 26 the the DET cana-3976 165 27 minority minority NOUN cana-3976 165 28 class class NOUN cana-3976 165 29 using use VERB cana-3976 165 30 smote smote NOUN cana-3976 165 31 to to PART cana-3976 165 32 balance balance VERB cana-3976 165 33 class class NOUN cana-3976 165 34 distribution distribution NOUN cana-3976 165 35 ; ; PUNCT cana-3976 165 36 ๐‘๐‘’๐‘ค_๐‘ƒ๐‘œ๐‘  ๐‘๐‘’๐‘ค_๐‘ƒ๐‘œ๐‘  X cana-3976 165 37 โ† โ† PROPN cana-3976 165 38 ๐‘†๐‘€๐‘‚๐‘‡๐ธ ๐‘†๐‘€๐‘‚๐‘‡๐ธ PROPN cana-3976 165 39 ( ( PUNCT cana-3976 165 40 ๐‘ƒ๐‘œ๐‘  ๐‘ƒ๐‘œ๐‘  PROPN cana-3976 165 41 , , PUNCT cana-3976 165 42 ๐‘)and ๐‘)and NOUN cana-3976 165 43 |๐‘๐‘’๐‘ค_๐‘ƒ๐‘œ๐‘ | |๐‘๐‘’๐‘ค_๐‘ƒ๐‘œ๐‘ | VERB cana-3976 165 44 = = SYM cana-3976 165 45 |๐‘๐‘’๐‘”| |๐‘๐‘’๐‘”| PROPN cana-3976 165 46 ; ; PUNCT cana-3976 165 47 communications communication NOUN cana-3976 165 48 on on ADP cana-3976 165 49 applied apply VERB cana-3976 165 50 nonlinear nonlinear ADJ cana-3976 165 51 analysis analysis NOUN cana-3976 165 52 issn issn NOUN cana-3976 165 53 : : PUNCT cana-3976 165 54 1074 1074 NUM cana-3976 165 55 - - PUNCT cana-3976 165 56 133x 133x NUM cana-3976 165 57 vol vol NOUN cana-3976 165 58 32 32 NUM cana-3976 165 59 no no NOUN cana-3976 165 60 . . PUNCT cana-3976 166 1 9s 9s NUM cana-3976 166 2 ( ( PUNCT cana-3976 166 3 2025 2025 NUM cana-3976 166 4 ) ) PUNCT cana-3976 167 1 709 709 NUM cana-3976 167 2 https://internationalpubls.com https://internationalpubls.com X cana-3976 167 3 ๐‘๐‘’๐‘ค_๐‘‡๐‘Ÿ ๐‘๐‘’๐‘ค_๐‘‡๐‘Ÿ X cana-3976 167 4 โ† โ† PROPN cana-3976 167 5 ๐‘๐‘’๐‘ค๐‘ƒ๐‘œ๐‘  ๐‘๐‘’๐‘ค๐‘ƒ๐‘œ๐‘  PROPN cana-3976 167 6 โˆช โˆช ADP cana-3976 167 7 ๐‘๐‘’๐‘” ๐‘๐‘’๐‘” PROPN cana-3976 167 8 for for ADP cana-3976 167 9 ๐‘ฅ๐œ– ๐‘ฅ๐œ– PROPN cana-3976 167 10 ๐‘๐‘’๐‘ค_๐‘‡๐‘Ÿdo ๐‘๐‘’๐‘ค_๐‘‡๐‘Ÿdo PUNCT cana-3976 167 11 compare compare VERB cana-3976 167 12 weighted weight VERB cana-3976 167 13 distances distance NOUN cana-3976 167 14 according accord VERB cana-3976 167 15 to to ADP cana-3976 167 16 ( ( PUNCT cana-3976 167 17 3 3 X cana-3976 167 18 ) ) PUNCT cana-3976 167 19 end end NOUN cana-3976 167 20 remove remove VERB cana-3976 167 21 noisy noisy ADJ cana-3976 167 22 examples example NOUN cana-3976 167 23 using use VERB cana-3976 167 24 enn enn PROPN cana-3976 167 25 based base VERB cana-3976 167 26 on on ADP cana-3976 167 27 the the DET cana-3976 167 28 weighted weighted ADJ cana-3976 167 29 distances distance NOUN cana-3976 167 30 : : PUNCT cana-3976 167 31 ๐‘๐‘’๐‘ค_๐‘‡๐‘Ÿ ๐‘๐‘’๐‘ค_๐‘‡๐‘Ÿ PROPN cana-3976 167 32 โ† โ† PROPN cana-3976 167 33 ๐ธ๐‘๐‘(๐‘๐‘’๐‘ค_๐‘‡๐‘Ÿ ๐ธ๐‘๐‘(๐‘๐‘’๐‘ค_๐‘‡๐‘Ÿ PROPN cana-3976 167 34 , , PUNCT cana-3976 167 35 ๐‘‘๐‘ค,๐‘˜ ๐‘‘๐‘ค,๐‘˜ NOUN cana-3976 167 36 ) ) PUNCT cana-3976 167 37 feature feature NOUN cana-3976 167 38 extraction extraction NOUN cana-3976 167 39 : : PUNCT cana-3976 167 40 we we PRON cana-3976 167 41 divided divide VERB cana-3976 167 42 the the DET cana-3976 167 43 416 416 NUM cana-3976 167 44 observations observation NOUN cana-3976 167 45 into into ADP cana-3976 167 46 208 208 NUM cana-3976 167 47 slices slice NOUN cana-3976 167 48 , , PUNCT cana-3976 167 49 each each PRON cana-3976 167 50 of of ADP cana-3976 167 51 which which PRON cana-3976 167 52 comprised comprise VERB cana-3976 167 53 176 176 NUM cana-3976 167 54 voxels voxel NOUN cana-3976 167 55 by by ADP cana-3976 167 56 176 176 NUM cana-3976 167 57 voxels voxel NOUN cana-3976 167 58 . . PUNCT cana-3976 168 1 the the DET cana-3976 168 2 analysis analysis NOUN cana-3976 168 3 used use VERB cana-3976 168 4 51 51 NUM cana-3976 168 5 of of ADP cana-3976 168 6 these these DET cana-3976 168 7 slices slice NOUN cana-3976 168 8 , , PUNCT cana-3976 168 9 ranging range VERB cana-3976 168 10 from from ADP cana-3976 168 11 78 78 NUM cana-3976 168 12 to to ADP cana-3976 168 13 128 128 NUM cana-3976 168 14 . . PUNCT cana-3976 169 1 these these DET cana-3976 169 2 slices slice NOUN cana-3976 169 3 were be AUX cana-3976 169 4 recovered recover VERB cana-3976 169 5 from from ADP cana-3976 169 6 the the DET cana-3976 169 7 original original ADJ cana-3976 169 8 format format NOUN cana-3976 169 9 and and CCONJ cana-3976 169 10 placed place VERB cana-3976 169 11 in in ADP cana-3976 169 12 a a DET cana-3976 169 13 new new ADJ cana-3976 169 14 location location NOUN cana-3976 169 15 as.png as.png PROPN cana-3976 169 16 files file NOUN cana-3976 169 17 with with ADP cana-3976 169 18 a a DET cana-3976 169 19 single single ADJ cana-3976 169 20 channel channel NOUN cana-3976 169 21 ( ( PUNCT cana-3976 169 22 gray gray ADJ cana-3976 169 23 - - PUNCT cana-3976 169 24 scale scale NOUN cana-3976 169 25 ) ) PUNCT cana-3976 169 26 . . PUNCT cana-3976 170 1 we we PRON cana-3976 170 2 replicated replicate VERB cana-3976 170 3 every every DET cana-3976 170 4 image image NOUN cana-3976 170 5 with with ADP cana-3976 170 6 its its PRON cana-3976 170 7 own own ADJ cana-3976 170 8 set set NOUN cana-3976 170 9 of of ADP cana-3976 170 10 corresponding correspond VERB cana-3976 170 11 classification classification NOUN cana-3976 170 12 labels label NOUN cana-3976 170 13 . . PUNCT cana-3976 171 1 the the DET cana-3976 171 2 images image NOUN cana-3976 171 3 were be AUX cana-3976 171 4 given give VERB cana-3976 171 5 a a DET cana-3976 171 6 random random ADJ cana-3976 171 7 transformation transformation NOUN cana-3976 171 8 after after ADP cana-3976 171 9 being be AUX cana-3976 171 10 padded pad VERB cana-3976 171 11 with with ADP cana-3976 171 12 three three NUM cana-3976 171 13 voxels voxel NOUN cana-3976 171 14 on on ADP cana-3976 171 15 all all DET cana-3976 171 16 sides side NOUN cana-3976 171 17 as as ADP cana-3976 171 18 part part NOUN cana-3976 171 19 of of ADP cana-3976 171 20 the the DET cana-3976 171 21 modeling modeling NOUN cana-3976 171 22 process process NOUN cana-3976 171 23 . . PUNCT cana-3976 172 1 there there PRON cana-3976 172 2 were be VERB cana-3976 172 3 only only ADV cana-3976 172 4 20,800 20,800 NUM cana-3976 172 5 mri mri NOUN cana-3976 172 6 images image NOUN cana-3976 172 7 , , PUNCT cana-3976 172 8 as as SCONJ cana-3976 172 9 opposed oppose VERB cana-3976 172 10 to to ADP cana-3976 172 11 51 51 NUM cana-3976 172 12 times time NOUN cana-3976 172 13 416 416 NUM cana-3976 172 14 , , PUNCT cana-3976 172 15 or or CCONJ cana-3976 172 16 21,216 21,216 NUM cana-3976 172 17 . . PUNCT cana-3976 173 1 even even ADV cana-3976 173 2 without without ADP cana-3976 173 3 accounting account VERB cana-3976 173 4 for for ADP cana-3976 173 5 the the DET cana-3976 173 6 one one NUM cana-3976 173 7 - - PUNCT cana-3976 173 8 of of ADP cana-3976 173 9 - - PUNCT cana-3976 173 10 a a DET cana-3976 173 11 - - PUNCT cana-3976 173 12 kind kind NOUN cana-3976 173 13 ( ( PUNCT cana-3976 173 14 and and CCONJ cana-3976 173 15 potentially potentially ADV cana-3976 173 16 infinite infinite ADJ cana-3976 173 17 ) ) PUNCT cana-3976 173 18 variations variation NOUN cana-3976 173 19 , , PUNCT cana-3976 173 20 the the DET cana-3976 173 21 total total ADJ cana-3976 173 22 number number NOUN cana-3976 173 23 of of ADP cana-3976 173 24 voxels voxel NOUN cana-3976 173 25 in in ADP cana-3976 173 26 the the DET cana-3976 173 27 photos photo NOUN cana-3976 173 28 exceeds exceed VERB cana-3976 173 29 640 640 NUM cana-3976 173 30 million million NUM cana-3976 173 31 . . PUNCT cana-3976 174 1 classification classification NOUN cana-3976 174 2 : : PUNCT cana-3976 174 3 this this DET cana-3976 174 4 paper paper NOUN cana-3976 174 5 used use VERB cana-3976 174 6 four four NUM cana-3976 174 7 ml ml NOUN cana-3976 174 8 approaches approach NOUN cana-3976 174 9 to to PART cana-3976 174 10 classify classify VERB cana-3976 174 11 alzheimer alzheimer PROPN cana-3976 174 12 's 's PART cana-3976 174 13 disease disease NOUN cana-3976 174 14 . . PUNCT cana-3976 175 1 decision decision NOUN cana-3976 175 2 tree tree NOUN cana-3976 175 3 classifier classifier NOUN cana-3976 175 4 : : PUNCT cana-3976 175 5 this this DET cana-3976 175 6 dataset dataset NOUN cana-3976 175 7 splits split VERB cana-3976 175 8 depending depend VERB cana-3976 175 9 on on ADP cana-3976 175 10 a a DET cana-3976 175 11 given give VERB cana-3976 175 12 constraint constraint NOUN cana-3976 175 13 to to PART cana-3976 175 14 optimize optimize VERB cana-3976 175 15 data datum NOUN cana-3976 175 16 separation separation NOUN cana-3976 175 17 and and CCONJ cana-3976 175 18 then then ADV cana-3976 175 19 displays display VERB cana-3976 175 20 it it PRON cana-3976 175 21 as as ADP cana-3976 175 22 a a DET cana-3976 175 23 tree tree NOUN cana-3976 175 24 [ [ X cana-3976 175 25 24 24 NUM cana-3976 175 26 ] ] PUNCT cana-3976 175 27 . . PUNCT cana-3976 176 1 this this DET cana-3976 176 2 approach approach NOUN cana-3976 176 3 generates generate VERB cana-3976 176 4 a a DET cana-3976 176 5 binary binary ADJ cana-3976 176 6 tree tree NOUN cana-3976 176 7 with with ADP cana-3976 176 8 two two NUM cana-3976 176 9 edges edge NOUN cana-3976 176 10 for for ADP cana-3976 176 11 each each DET cana-3976 176 12 node node NOUN cana-3976 176 13 . . PUNCT cana-3976 177 1 these these DET cana-3976 177 2 edges edge NOUN cana-3976 177 3 determine determine VERB cana-3976 177 4 the the DET cana-3976 177 5 most most ADV cana-3976 177 6 relevant relevant ADJ cana-3976 177 7 category category NOUN cana-3976 177 8 and and CCONJ cana-3976 177 9 numerical numerical ADJ cana-3976 177 10 features feature NOUN cana-3976 177 11 to to PART cana-3976 177 12 split split VERB cana-3976 177 13 based base VERB cana-3976 177 14 on on ADP cana-3976 177 15 acceptable acceptable ADJ cana-3976 177 16 impurity impurity NOUN cana-3976 177 17 criteria criterion NOUN cana-3976 177 18 . . PUNCT cana-3976 178 1 use use VERB cana-3976 178 2 the the DET cana-3976 178 3 gini gini NOUN cana-3976 178 4 and and CCONJ cana-3976 178 5 entropy entropy PROPN cana-3976 178 6 impureness impureness PROPN cana-3976 178 7 indices index NOUN cana-3976 178 8 for for ADP cana-3976 178 9 decision decision NOUN cana-3976 178 10 tree tree NOUN cana-3976 178 11 categorization categorization NOUN cana-3976 178 12 . . PUNCT cana-3976 179 1 gini gini PROPN cana-3976 179 2 represents represent VERB cana-3976 179 3 impurity impurity NOUN cana-3976 179 4 . . PUNCT cana-3976 180 1 โˆ‘ โˆ‘ PUNCT cana-3976 180 2 ๐‘“๐‘–(1 ๐‘“๐‘–(1 PROPN cana-3976 180 3 โˆ’ โˆ’ PROPN cana-3976 180 4 ๐‘“๐‘– ๐‘“๐‘– PROPN cana-3976 180 5 ) ) PUNCT cana-3976 180 6 ๐ถ ๐ถ PROPN cana-3976 180 7 ๐‘–=1 ๐‘–=1 PROPN cana-3976 180 8 ( ( PUNCT cana-3976 180 9 4 4 X cana-3976 180 10 ) ) PUNCT cana-3976 180 11 where where SCONJ cana-3976 180 12 ndenotes ndenote NOUN cana-3976 180 13 labels label NOUN cana-3976 180 14 and and CCONJ cana-3976 180 15 fidenoteslabel fidenoteslabel NOUN cana-3976 180 16 frequency frequency NOUN cana-3976 180 17 . . PUNCT cana-3976 181 1 โˆ‘ โˆ‘ PUNCT cana-3976 181 2 โˆ’๐‘“๐‘–๐‘™๐‘œ๐‘”(๐‘“๐‘– โˆ’๐‘“๐‘–๐‘™๐‘œ๐‘”(๐‘“๐‘– X cana-3976 181 3 ) ) PUNCT cana-3976 181 4 ๐ถ ๐ถ PROPN cana-3976 181 5 ๐‘–=1 ๐‘–=1 PROPN cana-3976 181 6 ( ( PUNCT cana-3976 181 7 5 5 X cana-3976 181 8 ) ) PUNCT cana-3976 181 9 support support NOUN cana-3976 181 10 vector vector NOUN cana-3976 181 11 machine machine NOUN cana-3976 181 12 classifier classifier NOUN cana-3976 181 13 : : PUNCT cana-3976 181 14 support support NOUN cana-3976 181 15 vector vector NOUN cana-3976 181 16 machines machine NOUN cana-3976 181 17 are be AUX cana-3976 181 18 methods method NOUN cana-3976 181 19 for for ADP cana-3976 181 20 supervised supervised ADJ cana-3976 181 21 learning learning NOUN cana-3976 181 22 that that PRON cana-3976 181 23 can can AUX cana-3976 181 24 be be AUX cana-3976 181 25 used use VERB cana-3976 181 26 to to PART cana-3976 181 27 tackle tackle VERB cana-3976 181 28 classification classification NOUN cana-3976 181 29 and and CCONJ cana-3976 181 30 regression regression NOUN cana-3976 181 31 problems problem NOUN cana-3976 181 32 . . PUNCT cana-3976 182 1 we we PRON cana-3976 182 2 know know VERB cana-3976 182 3 these these DET cana-3976 182 4 machines machine NOUN cana-3976 182 5 as as ADP cana-3976 182 6 svms svms NOUN cana-3976 182 7 . . PUNCT cana-3976 183 1 the the DET cana-3976 183 2 conventional conventional ADJ cana-3976 183 3 support support NOUN cana-3976 183 4 vector vector NOUN cana-3976 183 5 machine machine NOUN cana-3976 183 6 ( ( PUNCT cana-3976 183 7 svm svm PROPN cana-3976 183 8 ) ) PUNCT cana-3976 183 9 , , PUNCT cana-3976 183 10 currently currently ADV cana-3976 183 11 the the DET cana-3976 183 12 most most ADV cana-3976 183 13 widely widely ADV cana-3976 183 14 used use VERB cana-3976 183 15 binary binary ADJ cana-3976 183 16 classification classification NOUN cana-3976 183 17 technique technique NOUN cana-3976 183 18 , , PUNCT cana-3976 183 19 was be AUX cana-3976 183 20 applied apply VERB cana-3976 183 21 to to ADP cana-3976 183 22 structural structural ADJ cana-3976 183 23 mri mri NOUN cana-3976 183 24 scan scan NOUN cana-3976 183 25 pictures picture NOUN cana-3976 183 26 for for ADP cana-3976 183 27 disease disease NOUN cana-3976 183 28 prediction prediction NOUN cana-3976 183 29 . . PUNCT cana-3976 184 1 the the DET cana-3976 184 2 svm svm PROPN cana-3976 184 3 is be AUX cana-3976 184 4 a a DET cana-3976 184 5 machine machine NOUN cana-3976 184 6 learning learn VERB cana-3976 184 7 classifier classifier NOUN cana-3976 184 8 that that PRON cana-3976 184 9 uses use VERB cana-3976 184 10 a a DET cana-3976 184 11 vector vector NOUN cana-3976 184 12 of of ADP cana-3976 184 13 predictions prediction NOUN cana-3976 184 14 to to PART cana-3976 184 15 translate translate VERB cana-3976 184 16 it it PRON cana-3976 184 17 into into ADP cana-3976 184 18 a a DET cana-3976 184 19 higher higher ADV cana-3976 184 20 - - PUNCT cana-3976 184 21 dimensional dimensional ADJ cana-3976 184 22 plane plane NOUN cana-3976 184 23 . . PUNCT cana-3976 185 1 we we PRON cana-3976 185 2 achieve achieve VERB cana-3976 185 3 this this PRON cana-3976 185 4 by by ADP cana-3976 185 5 using use VERB cana-3976 185 6 communications communication NOUN cana-3976 185 7 on on ADP cana-3976 185 8 applied apply VERB cana-3976 185 9 nonlinear nonlinear ADJ cana-3976 185 10 analysis analysis NOUN cana-3976 185 11 issn issn NOUN cana-3976 185 12 : : PUNCT cana-3976 185 13 1074 1074 NUM cana-3976 185 14 - - PUNCT cana-3976 185 15 133x 133x NUM cana-3976 185 16 vol vol NOUN cana-3976 185 17 32 32 NUM cana-3976 185 18 no no NOUN cana-3976 185 19 . . PUNCT cana-3976 186 1 9s 9s NUM cana-3976 186 2 ( ( PUNCT cana-3976 186 3 2025 2025 NUM cana-3976 186 4 ) ) PUNCT cana-3976 186 5 710 710 NUM cana-3976 186 6 https://internationalpubls.com https://internationalpubls.com X cana-3976 186 7 two two NUM cana-3976 186 8 distinct distinct ADJ cana-3976 186 9 linear linear ADJ cana-3976 186 10 or or CCONJ cana-3976 186 11 nonlinear nonlinear ADJ cana-3976 186 12 kernel kernel PROPN cana-3976 186 13 functions function NOUN cana-3976 186 14 . . PUNCT cana-3976 187 1 the the DET cana-3976 187 2 binary binary PROPN cana-3976 187 3 classification classification NOUN cana-3976 187 4 problem problem NOUN cana-3976 187 5 , , PUNCT cana-3976 187 6 according accord VERB cana-3976 187 7 to to ADP cana-3976 187 8 the the DET cana-3976 187 9 concept concept NOUN cana-3976 187 10 of of ADP cana-3976 187 11 structural structural ADJ cana-3976 187 12 risk risk NOUN cana-3976 187 13 minimization minimization NOUN cana-3976 187 14 [ [ X cana-3976 187 15 25 25 NUM cana-3976 187 16 ] ] PUNCT cana-3976 187 17 , , PUNCT cana-3976 187 18 involves involve VERB cana-3976 187 19 two two NUM cana-3976 187 20 classes class NOUN cana-3976 187 21 ( ( PUNCT cana-3976 187 22 +1 +1 NOUN cana-3976 187 23 or or CCONJ cana-3976 187 24 1 1 NUM cana-3976 187 25 ) ) PUNCT cana-3976 187 26 , , PUNCT cana-3976 187 27 and and CCONJ cana-3976 187 28 it it PRON cana-3976 187 29 is be AUX cana-3976 187 30 simple simple ADJ cana-3976 187 31 to to PART cana-3976 187 32 determine determine VERB cana-3976 187 33 from from ADP cana-3976 187 34 one one NUM cana-3976 187 35 another another DET cana-3976 187 36 in in ADP cana-3976 187 37 a a DET cana-3976 187 38 hyperplane hyperplane NOUN cana-3976 187 39 . . PUNCT cana-3976 188 1 using use VERB cana-3976 188 2 training training NOUN cana-3976 188 3 data datum NOUN cana-3976 188 4 , , PUNCT cana-3976 188 5 svms svms NOUN cana-3976 188 6 are be AUX cana-3976 188 7 supposed suppose VERB cana-3976 188 8 to to PART cana-3976 188 9 build build VERB cana-3976 188 10 a a DET cana-3976 188 11 discriminating discriminate VERB cana-3976 188 12 function function NOUN cana-3976 188 13 capable capable ADJ cana-3976 188 14 of of ADP cana-3976 188 15 accurately accurately ADV cana-3976 188 16 classifying classify VERB cana-3976 188 17 new new ADJ cana-3976 188 18 samples sample NOUN cana-3976 188 19 ( ( PUNCT cana-3976 188 20 m m NOUN cana-3976 188 21 , , PUNCT cana-3976 188 22 n n CCONJ cana-3976 188 23 ) ) PUNCT cana-3976 188 24 . . PUNCT cana-3976 189 1 we we PRON cana-3976 189 2 can can AUX cana-3976 189 3 use use VERB cana-3976 189 4 these these PRON cana-3976 189 5 in in ADP cana-3976 189 6 conjunction conjunction NOUN cana-3976 189 7 with with ADP cana-3976 189 8 kernel kernel PROPN cana-3976 189 9 models model NOUN cana-3976 189 10 to to PART cana-3976 189 11 separate separate VERB cana-3976 189 12 data datum NOUN cana-3976 189 13 efficiently efficiently ADV cana-3976 189 14 . . PUNCT cana-3976 190 1 as as ADP cana-3976 190 2 a a DET cana-3976 190 3 result result NOUN cana-3976 190 4 , , PUNCT cana-3976 190 5 that that SCONJ cana-3976 190 6 hyperplane hyperplane NOUN cana-3976 190 7 can can AUX cana-3976 190 8 communicate communicate VERB cana-3976 190 9 with with ADP cana-3976 190 10 a a DET cana-3976 190 11 nonlinear nonlinear ADJ cana-3976 190 12 decision decision NOUN cana-3976 190 13 boundary boundary ADJ cana-3976 190 14 while while SCONJ cana-3976 190 15 defining define VERB cana-3976 190 16 svms svms NOUN cana-3976 190 17 using use VERB cana-3976 190 18 support support NOUN cana-3976 190 19 vectors vector NOUN cana-3976 190 20 : : PUNCT cana-3976 190 21 ๐‘“(๐‘š ๐‘“(๐‘š X cana-3976 190 22 ) ) PUNCT cana-3976 190 23 = = SYM cana-3976 190 24 ๐‘ ๐‘–๐‘”๐‘› ๐‘ ๐‘–๐‘”๐‘› NOUN cana-3976 190 25 ( ( PUNCT cana-3976 190 26 โˆ‘ โˆ‘ PUNCT cana-3976 190 27 ๐‘Ž๐‘–๐‘ฆ๐‘– ๐‘Ž๐‘–๐‘ฆ๐‘– PROPN cana-3976 190 28 ๐พ(๐‘ ๐‘– ๐พ(๐‘ ๐‘– NOUN cana-3976 190 29 , , PUNCT cana-3976 190 30 ๐‘ฅ ๐‘ฅ NOUN cana-3976 190 31 ) ) PUNCT cana-3976 190 32 ) ) PUNCT cana-3976 191 1 + + CCONJ cana-3976 191 2 ๐‘ค0 ๐‘ค0 NOUN cana-3976 191 3 ( ( PUNCT cana-3976 191 4 6 6 NUM cana-3976 191 5 ) ) PUNCT cana-3976 191 6 where where SCONJ cana-3976 191 7 k k PROPN cana-3976 191 8 is be AUX cana-3976 191 9 a a DET cana-3976 191 10 kernel kernel NOUN cana-3976 191 11 term term NOUN cana-3976 191 12 and and CCONJ cana-3976 191 13 si si X cana-3976 191 14 is be AUX cana-3976 191 15 the the DET cana-3976 191 16 support support NOUN cana-3976 191 17 vectors vector NOUN cana-3976 191 18 and and CCONJ cana-3976 191 19 ai ai VERB cana-3976 191 20 is be AUX cana-3976 191 21 a a DET cana-3976 191 22 weight weight NOUN cana-3976 191 23 constant constant ADJ cana-3976 192 1 [ [ X cana-3976 192 2 26 26 NUM cana-3976 192 3 ] ] PUNCT cana-3976 192 4 . . PUNCT cana-3976 193 1 gradient gradient PROPN cana-3976 193 2 boosted boost VERB cana-3976 193 3 tree tree NOUN cana-3976 193 4 ensembles ensemble NOUN cana-3976 193 5 ( ( PUNCT cana-3976 193 6 gradient gradient ADJ cana-3976 193 7 boosting boosting NOUN cana-3976 193 8 ): ): PUNCT cana-3976 193 9 in in ADP cana-3976 193 10 this this PRON cana-3976 193 11 , , PUNCT cana-3976 193 12 the the DET cana-3976 193 13 mmse mmse ADJ cana-3976 193 14 and and CCONJ cana-3976 193 15 socio socio ADJ cana-3976 193 16 - - ADJ cana-3976 193 17 demographic demographic ADJ cana-3976 193 18 data datum NOUN cana-3976 193 19 were be AUX cana-3976 193 20 used use VERB cana-3976 193 21 to to PART cana-3976 193 22 categorize categorize VERB cana-3976 193 23 ad ad NOUN cana-3976 193 24 . . PUNCT cana-3976 194 1 this this DET cana-3976 194 2 model model NOUN cana-3976 194 3 improves improve VERB cana-3976 194 4 prediction prediction NOUN cana-3976 194 5 accuracy accuracy NOUN cana-3976 194 6 by by ADP cana-3976 194 7 building build VERB cana-3976 194 8 weaker weak ADJ cana-3976 194 9 decision decision NOUN cana-3976 194 10 and and CCONJ cana-3976 194 11 classification classification NOUN cana-3976 194 12 tree tree NOUN cana-3976 194 13 models model NOUN cana-3976 194 14 one one NUM cana-3976 194 15 after after ADP cana-3976 194 16 the the DET cana-3976 194 17 other other ADJ cana-3976 194 18 . . PUNCT cana-3976 195 1 we we PRON cana-3976 195 2 have have AUX cana-3976 195 3 also also ADV cana-3976 195 4 known know VERB cana-3976 195 5 this this DET cana-3976 195 6 model model NOUN cana-3976 195 7 as as ADP cana-3976 195 8 a a DET cana-3976 195 9 gradient gradient NOUN cana-3976 195 10 - - PUNCT cana-3976 195 11 boosted boost VERB cana-3976 195 12 machine machine NOUN cana-3976 195 13 ( ( PUNCT cana-3976 195 14 gbm gbm NOUN cana-3976 195 15 ) ) PUNCT cana-3976 195 16 . . PUNCT cana-3976 196 1 a a DET cana-3976 196 2 classification classification NOUN cana-3976 196 3 tree tree NOUN cana-3976 196 4 model model NOUN cana-3976 196 5 aims aim VERB cana-3976 196 6 to to PART cana-3976 196 7 construct construct VERB cana-3976 196 8 a a DET cana-3976 196 9 decision decision NOUN cana-3976 196 10 tree tree NOUN cana-3976 196 11 capable capable ADJ cana-3976 196 12 of of ADP cana-3976 196 13 delivering deliver VERB cana-3976 196 14 a a DET cana-3976 196 15 classification classification NOUN cana-3976 196 16 vote vote NOUN cana-3976 196 17 . . PUNCT cana-3976 197 1 we we PRON cana-3976 197 2 accomplish accomplish VERB cana-3976 197 3 this this PRON cana-3976 197 4 by by ADP cana-3976 197 5 dividing divide VERB cana-3976 197 6 the the DET cana-3976 197 7 independent independent ADJ cana-3976 197 8 variables variable NOUN cana-3976 197 9 throughout throughout ADP cana-3976 197 10 the the DET cana-3976 197 11 model model NOUN cana-3976 197 12 . . PUNCT cana-3976 198 1 the the DET cana-3976 198 2 gini gini PROPN cana-3976 198 3 impurity impurity NOUN cana-3976 198 4 or or CCONJ cana-3976 198 5 cross cross ADJ cana-3976 198 6 - - ADJ cana-3976 198 7 entropy entropy ADJ cana-3976 198 8 equations equation NOUN cana-3976 198 9 ( ( PUNCT cana-3976 198 10 eq eq NOUN cana-3976 198 11 . . PROPN cana-3976 198 12 7 7 NUM cana-3976 198 13 and and CCONJ cana-3976 198 14 8) 8) NUM cana-3976 199 1 [ [ X cana-3976 199 2 27 27 NUM cana-3976 199 3 , , PUNCT cana-3976 199 4 28 28 NUM cana-3976 199 5 ] ] PUNCT cana-3976 199 6 are be AUX cana-3976 199 7 commonly commonly ADV cana-3976 199 8 employed employ VERB cana-3976 199 9 to to PART cana-3976 199 10 determine determine VERB cana-3976 199 11 such such ADJ cana-3976 199 12 splits split NOUN cana-3976 199 13 . . PUNCT cana-3976 200 1 in in ADP cana-3976 200 2 these these DET cana-3976 200 3 equations equation NOUN cana-3976 200 4 , , PUNCT cana-3976 200 5 k k PROPN cana-3976 200 6 represents represent VERB cana-3976 200 7 the the DET cana-3976 200 8 total total ADJ cana-3976 200 9 number number NOUN cana-3976 200 10 of of ADP cana-3976 200 11 classes class NOUN cana-3976 200 12 , , PUNCT cana-3976 200 13 and and CCONJ cana-3976 200 14 pi pi NOUN cana-3976 200 15 represents represent VERB cana-3976 200 16 the the DET cana-3976 200 17 percentage percentage NOUN cana-3976 200 18 of of ADP cana-3976 200 19 total total ADJ cana-3976 200 20 cases case NOUN cana-3976 200 21 that that PRON cana-3976 200 22 belong belong VERB cana-3976 200 23 to to ADP cana-3976 200 24 a a DET cana-3976 200 25 specific specific ADJ cana-3976 200 26 class class NOUN cana-3976 200 27 . . PUNCT cana-3976 201 1 ๐บ๐‘–๐‘›๐‘– ๐บ๐‘–๐‘›๐‘– VERB cana-3976 201 2 ๐‘–๐‘š๐‘๐‘ข๐‘Ÿ๐‘–๐‘ก๐‘ฆ ๐‘–๐‘š๐‘๐‘ข๐‘Ÿ๐‘–๐‘ก๐‘ฆ NOUN cana-3976 201 3 = = PUNCT cana-3976 201 4 โˆ‘ โˆ‘ PUNCT cana-3976 201 5 ๐‘๐‘–(1 ๐‘๐‘–(1 NOUN cana-3976 201 6 โˆ’ โˆ’ PROPN cana-3976 201 7 ๐‘๐‘– ๐‘๐‘– NOUN cana-3976 201 8 ) ) PUNCT cana-3976 201 9 ( ( PUNCT cana-3976 201 10 7 7 X cana-3976 201 11 ) ) PUNCT cana-3976 201 12 ๐‘˜ ๐‘˜ DET cana-3976 201 13 ๐‘–=1 ๐‘–=1 PROPN cana-3976 201 14 ๐ถ๐‘Ÿ๐‘œ๐‘ ๐‘  ๐ถ๐‘Ÿ๐‘œ๐‘ ๐‘  NOUN cana-3976 201 15 โˆ’ โˆ’ NOUN cana-3976 201 16 ๐‘’๐‘›๐‘ก๐‘Ÿ๐‘œ๐‘๐‘ฆ ๐‘’๐‘›๐‘ก๐‘Ÿ๐‘œ๐‘๐‘ฆ NOUN cana-3976 201 17 = = PUNCT cana-3976 202 1 โˆ’ โˆ’ NOUN cana-3976 202 2 โˆ‘ โˆ‘ PUNCT cana-3976 202 3 ๐‘๐‘–๐‘™๐‘œ๐‘”๐‘๐‘– ๐‘๐‘–๐‘™๐‘œ๐‘”๐‘๐‘– VERB cana-3976 202 4 ๐‘˜ ๐‘˜ X cana-3976 202 5 ๐‘–=1 ๐‘–=1 PROPN cana-3976 202 6 ( ( PUNCT cana-3976 202 7 8) 8) NUM cana-3976 202 8 using use VERB cana-3976 202 9 these these DET cana-3976 202 10 equations equation NOUN cana-3976 202 11 , , PUNCT cana-3976 202 12 the the DET cana-3976 202 13 splitting splitting NOUN cana-3976 202 14 algorithm algorithm NOUN cana-3976 202 15 makes make VERB cana-3976 202 16 an an DET cana-3976 202 17 aggressive aggressive ADJ cana-3976 202 18 , , PUNCT cana-3976 202 19 greedy greedy ADJ cana-3976 202 20 attempt attempt NOUN cana-3976 202 21 to to PART cana-3976 202 22 establish establish VERB cana-3976 202 23 homogeneity homogeneity NOUN cana-3976 202 24 . . PUNCT cana-3976 203 1 pruning prune VERB cana-3976 203 2 keeps keep VERB cana-3976 203 3 the the DET cana-3976 203 4 trees tree NOUN cana-3976 203 5 from from ADP cana-3976 203 6 becoming becoming AUX cana-3976 203 7 overburdened overburden VERB cana-3976 203 8 by by ADP cana-3976 203 9 restrictive restrictive ADJ cana-3976 203 10 branches branch NOUN cana-3976 203 11 , , PUNCT cana-3976 203 12 and and CCONJ cana-3976 203 13 they they PRON cana-3976 203 14 show show VERB cana-3976 203 15 its its PRON cana-3976 203 16 overview overview NOUN cana-3976 203 17 in in ADP cana-3976 203 18 figure figure NOUN cana-3976 203 19 2 2 NUM cana-3976 203 20 . . PUNCT cana-3976 203 21 figure figure NOUN cana-3976 203 22 2 2 NUM cana-3976 203 23 : : PUNCT cana-3976 203 24 overview overview NOUN cana-3976 203 25 of of ADP cana-3976 203 26 classification classification NOUN cana-3976 203 27 communications communication NOUN cana-3976 203 28 on on ADP cana-3976 203 29 applied apply VERB cana-3976 203 30 nonlinear nonlinear ADJ cana-3976 203 31 analysis analysis NOUN cana-3976 203 32 issn issn NOUN cana-3976 203 33 : : PUNCT cana-3976 203 34 1074 1074 NUM cana-3976 203 35 - - PUNCT cana-3976 203 36 133x 133x NUM cana-3976 203 37 vol vol NOUN cana-3976 203 38 32 32 NUM cana-3976 204 1 no no NOUN cana-3976 204 2 . . PUNCT cana-3976 205 1 9s 9s NUM cana-3976 205 2 ( ( PUNCT cana-3976 205 3 2025 2025 NUM cana-3976 205 4 ) ) PUNCT cana-3976 205 5 711 711 NUM cana-3976 205 6 https://internationalpubls.com https://internationalpubls.com X cana-3976 205 7 3.2 3.2 NUM cana-3976 205 8 proposed propose VERB cana-3976 205 9 classification classification NOUN cana-3976 205 10 method method NOUN cana-3976 205 11 : : PUNCT cana-3976 205 12 extra extra ADJ cana-3976 205 13 trees tree NOUN cana-3976 205 14 algorithm algorithm NOUN cana-3976 205 15 ( ( PUNCT cana-3976 205 16 eta eta PROPN cana-3976 205 17 ) ) PUNCT cana-3976 205 18 the the DET cana-3976 205 19 approach approach NOUN cana-3976 205 20 gets get VERB cana-3976 205 21 its its PRON cana-3976 205 22 name name NOUN cana-3976 205 23 from from ADP cana-3976 205 24 the the DET cana-3976 205 25 randomness randomness NOUN cana-3976 205 26 with with ADP cana-3976 205 27 which which PRON cana-3976 205 28 we we PRON cana-3976 205 29 generate generate VERB cana-3976 205 30 each each DET cana-3976 205 31 dt dt PROPN cana-3976 205 32 . . PUNCT cana-3976 206 1 the the DET cana-3976 206 2 fundamental fundamental ADJ cana-3976 206 3 goal goal NOUN cana-3976 206 4 of of ADP cana-3976 206 5 the the DET cana-3976 206 6 endeavor endeavor NOUN cana-3976 206 7 to to PART cana-3976 206 8 handle handle VERB cana-3976 206 9 numerically numerically ADV cana-3976 206 10 valued value VERB cana-3976 206 11 features feature NOUN cana-3976 206 12 was be AUX cana-3976 206 13 to to PART cana-3976 206 14 lessen lessen VERB cana-3976 206 15 the the DET cana-3976 206 16 likelihood likelihood NOUN cana-3976 206 17 of of ADP cana-3976 206 18 the the DET cana-3976 206 19 model model NOUN cana-3976 206 20 overfitting overfitte VERB cana-3976 206 21 to to ADP cana-3976 206 22 the the DET cana-3976 206 23 data datum NOUN cana-3976 206 24 . . PUNCT cana-3976 207 1 the the DET cana-3976 207 2 extra extra ADJ cana-3976 207 3 trees tree NOUN cana-3976 207 4 algorithm algorithm NOUN cana-3976 207 5 's 's PART cana-3976 207 6 functionality functionality NOUN cana-3976 207 7 is be AUX cana-3976 207 8 based base VERB cana-3976 207 9 on on ADP cana-3976 207 10 training train VERB cana-3976 207 11 a a DET cana-3976 207 12 set set NOUN cana-3976 207 13 of of ADP cana-3976 207 14 binary binary ADJ cana-3976 207 15 decision decision NOUN cana-3976 207 16 trees tree NOUN cana-3976 207 17 ( ( PUNCT cana-3976 207 18 dts dts NOUN cana-3976 207 19 ) ) PUNCT cana-3976 207 20 . . PUNCT cana-3976 208 1 the the DET cana-3976 208 2 accuracy accuracy NOUN cana-3976 208 3 of of ADP cana-3976 208 4 the the DET cana-3976 208 5 ensemble ensemble NOUN cana-3976 208 6 's 's PART cana-3976 208 7 predictions prediction NOUN cana-3976 208 8 can can AUX cana-3976 208 9 be be AUX cana-3976 208 10 attributed attribute VERB cana-3976 208 11 to to ADP cana-3976 208 12 the the DET cana-3976 208 13 fact fact NOUN cana-3976 208 14 that that SCONJ cana-3976 208 15 each each DET cana-3976 208 16 dt dt NOUN cana-3976 208 17 should should AUX cana-3976 208 18 be be AUX cana-3976 208 19 classified classify VERB cana-3976 208 20 . . PUNCT cana-3976 209 1 during during ADP cana-3976 209 2 the the DET cana-3976 209 3 dt dt NOUN cana-3976 209 4 training training NOUN cana-3976 209 5 phase phase NOUN cana-3976 209 6 , , PUNCT cana-3976 209 7 the the DET cana-3976 209 8 procedure procedure NOUN cana-3976 209 9 arbitrarily arbitrarily ADV cana-3976 209 10 selects select VERB cana-3976 209 11 numerous numerous ADJ cana-3976 209 12 data datum NOUN cana-3976 209 13 columns column NOUN cana-3976 209 14 without without ADP cana-3976 209 15 replacing replace VERB cana-3976 209 16 any any PRON cana-3976 209 17 of of ADP cana-3976 209 18 them they PRON cana-3976 209 19 and and CCONJ cana-3976 209 20 will will AUX cana-3976 209 21 attempts attempt VERB cana-3976 209 22 to to PART cana-3976 209 23 identify identify VERB cana-3976 209 24 which which DET cana-3976 209 25 column column NOUN cana-3976 209 26 best well ADV cana-3976 209 27 depicts depict VERB cana-3976 209 28 the the DET cana-3976 209 29 data datum NOUN cana-3976 209 30 . . PUNCT cana-3976 210 1 each each DET cana-3976 210 2 column column NOUN cana-3976 210 3 has have VERB cana-3976 210 4 a a DET cana-3976 210 5 distinct distinct ADJ cana-3976 210 6 feature feature NOUN cana-3976 210 7 that that PRON cana-3976 210 8 goes go VERB cana-3976 210 9 deeper deeply ADV cana-3976 210 10 into into ADP cana-3976 210 11 a a DET cana-3976 210 12 particular particular ADJ cana-3976 210 13 aspect aspect NOUN cana-3976 210 14 of of ADP cana-3976 210 15 the the DET cana-3976 210 16 collected collect VERB cana-3976 210 17 data datum NOUN cana-3976 210 18 . . PUNCT cana-3976 211 1 we we PRON cana-3976 211 2 used use VERB cana-3976 211 3 the the DET cana-3976 211 4 gini gini PROPN cana-3976 211 5 index index PROPN cana-3976 211 6 , , PUNCT cana-3976 211 7 a a DET cana-3976 211 8 derivative derivative NOUN cana-3976 211 9 of of ADP cana-3976 211 10 a a DET cana-3976 211 11 different different ADJ cana-3976 211 12 scoring scoring NOUN cana-3976 211 13 approach approach NOUN cana-3976 211 14 entirely entirely ADV cana-3976 211 15 . . PUNCT cana-3976 212 1 we we PRON cana-3976 212 2 rated rate VERB cana-3976 212 3 the the DET cana-3976 212 4 various various ADJ cana-3976 212 5 data data NOUN cana-3976 212 6 sets set NOUN cana-3976 212 7 based base VERB cana-3976 212 8 on on ADP cana-3976 212 9 their their PRON cana-3976 212 10 performance performance NOUN cana-3976 212 11 on on ADP cana-3976 212 12 the the DET cana-3976 212 13 gini gini PROPN cana-3976 212 14 index index PROPN cana-3976 212 15 . . PUNCT cana-3976 213 1 the the DET cana-3976 213 2 gini gini PROPN cana-3976 213 3 index index NOUN cana-3976 213 4 is be AUX cana-3976 213 5 a a DET cana-3976 213 6 value value NOUN cana-3976 213 7 ranging range VERB cana-3976 213 8 from from ADP cana-3976 213 9 0 0 NUM cana-3976 213 10 to to ADP cana-3976 213 11 1 1 NUM cana-3976 213 12 that that PRON cana-3976 213 13 indicates indicate VERB cana-3976 213 14 the the DET cana-3976 213 15 likelihood likelihood NOUN cana-3976 213 16 of of ADP cana-3976 213 17 erroneously erroneously ADV cana-3976 213 18 classifying classify VERB cana-3976 213 19 the the DET cana-3976 213 20 data datum NOUN cana-3976 213 21 if if SCONJ cana-3976 213 22 we we PRON cana-3976 213 23 choose choose VERB cana-3976 213 24 a a DET cana-3976 213 25 classification classification NOUN cana-3976 213 26 at at ADP cana-3976 213 27 random random ADJ cana-3976 213 28 in in ADP cana-3976 213 29 proportion proportion NOUN cana-3976 213 30 to to ADP cana-3976 213 31 what what PRON cana-3976 213 32 is be AUX cana-3976 213 33 currently currently ADV cana-3976 213 34 present present ADJ cana-3976 213 35 in in ADP cana-3976 213 36 the the DET cana-3976 213 37 data datum NOUN cana-3976 213 38 . . PUNCT cana-3976 214 1 this this DET cana-3976 214 2 number number NOUN cana-3976 214 3 is be AUX cana-3976 214 4 a a DET cana-3976 214 5 percentage percentage NOUN cana-3976 214 6 that that PRON cana-3976 214 7 ranges range VERB cana-3976 214 8 between between ADP cana-3976 214 9 0 0 NUM cana-3976 214 10 and and CCONJ cana-3976 214 11 1 1 NUM cana-3976 214 12 . . PUNCT cana-3976 215 1 given give VERB cana-3976 215 2 these these DET cana-3976 215 3 considerations consideration NOUN cana-3976 215 4 , , PUNCT cana-3976 215 5 we we PRON cana-3976 215 6 aim aim VERB cana-3976 215 7 to to PART cana-3976 215 8 discover discover VERB cana-3976 215 9 which which DET cana-3976 215 10 category category NOUN cana-3976 215 11 has have VERB cana-3976 215 12 the the DET cana-3976 215 13 lowest low ADJ cana-3976 215 14 gini gini NOUN cana-3976 215 15 index index NOUN cana-3976 215 16 value value NOUN cana-3976 215 17 . . PUNCT cana-3976 216 1 when when SCONJ cana-3976 216 2 applied apply VERB cana-3976 216 3 to to ADP cana-3976 216 4 a a DET cana-3976 216 5 specific specific ADJ cana-3976 216 6 division division NOUN cana-3976 216 7 , , PUNCT cana-3976 216 8 the the DET cana-3976 216 9 gini gini PROPN cana-3976 216 10 index index NOUN cana-3976 216 11 is be AUX cana-3976 216 12 defined define VERB cana-3976 216 13 as as ADP cana-3976 216 14 follows follow VERB cana-3976 216 15 : : PUNCT cana-3976 216 16 ๐บ(๐ด๐‘— ๐บ(๐ด๐‘— NUM cana-3976 216 17 ) ) PUNCT cana-3976 216 18 = = SYM cana-3976 216 19 1 1 NUM cana-3976 216 20 โˆ’ โˆ’ NOUN cana-3976 216 21 โˆ‘ โˆ‘ PROPN cana-3976 216 22 ( ( PUNCT cana-3976 216 23 โŒˆ๐‘†๐‘–โŒ‰ โŒˆ๐‘†๐‘–โŒ‰ NOUN cana-3976 216 24 |๐‘†| |๐‘†| VERB cana-3976 216 25 โˆ‘ โˆ‘ PUNCT cana-3976 216 26 ( ( PUNCT cana-3976 216 27 ( ( PUNCT cana-3976 216 28 ๐‘๐‘–,๐‘— ๐‘๐‘–,๐‘— NOUN cana-3976 216 29 ) ) PUNCT cana-3976 216 30 2 2 NUM cana-3976 216 31 ) ) PUNCT cana-3976 216 32 ๐ถ ๐ถ PROPN cana-3976 216 33 ๐‘—=1 ๐‘—=1 PROPN cana-3976 216 34 ) ) PUNCT cana-3976 216 35 2 2 NUM cana-3976 216 36 ๐‘–=1 ๐‘–=1 PUNCT cana-3976 216 37 where where SCONJ cana-3976 216 38 s s NOUN cana-3976 216 39 represents represent VERB cana-3976 216 40 the the DET cana-3976 216 41 existing exist VERB cana-3976 216 42 data datum NOUN cana-3976 216 43 set set VERB cana-3976 216 44 , , PUNCT cana-3976 216 45 si si PROPN cana-3976 216 46 represents represent VERB cana-3976 216 47 one one NUM cana-3976 216 48 dataset dataset NOUN cana-3976 216 49 , , PUNCT cana-3976 216 50 c c PROPN cana-3976 216 51 represents represent VERB cana-3976 216 52 the the DET cana-3976 216 53 total total ADJ cana-3976 216 54 classifications classification NOUN cana-3976 216 55 , , PUNCT cana-3976 216 56 and and CCONJ cana-3976 216 57 pi pi NOUN cana-3976 216 58 , , PUNCT cana-3976 216 59 j j PROPN cana-3976 216 60 represents represent VERB cana-3976 216 61 the the DET cana-3976 216 62 proportion proportion NOUN cana-3976 216 63 of of ADP cana-3976 216 64 the the DET cana-3976 216 65 ith ith PROPN cana-3976 216 66 data datum NOUN cana-3976 216 67 subset subset NOUN cana-3976 216 68 represented represent VERB cana-3976 216 69 by by ADP cana-3976 216 70 the the DET cana-3976 216 71 j j PROPN cana-3976 216 72 - - PUNCT cana-3976 216 73 th th VERB cana-3976 216 74 classification classification NOUN cana-3976 216 75 . . PUNCT cana-3976 217 1 the the DET cana-3976 217 2 structure structure NOUN cana-3976 217 3 of of ADP cana-3976 217 4 the the DET cana-3976 217 5 tree tree NOUN cana-3976 217 6 is be AUX cana-3976 217 7 then then ADV cana-3976 217 8 built build VERB cana-3976 217 9 recursively recursively ADV cana-3976 217 10 using use VERB cana-3976 217 11 the the DET cana-3976 217 12 same same ADJ cana-3976 217 13 fundamentals fundamental NOUN cana-3976 217 14 until until SCONJ cana-3976 217 15 one one NUM cana-3976 217 16 of of ADP cana-3976 217 17 the the DET cana-3976 217 18 three three NUM cana-3976 217 19 conditions condition NOUN cana-3976 217 20 is be AUX cana-3976 217 21 met meet VERB cana-3976 217 22 : : PUNCT cana-3976 218 1 1 1 X cana-3976 218 2 . . X cana-3976 219 1 all all DET cana-3976 219 2 class class NOUN cana-3976 219 3 labels label NOUN cana-3976 219 4 in in ADP cana-3976 219 5 the the DET cana-3976 219 6 node node NOUN cana-3976 219 7 's 's PART cana-3976 219 8 subset subset NOUN cana-3976 219 9 of of ADP cana-3976 219 10 data datum NOUN cana-3976 219 11 are be AUX cana-3976 219 12 the the DET cana-3976 219 13 similar similar ADJ cana-3976 219 14 . . PUNCT cana-3976 220 1 2 2 X cana-3976 220 2 . . X cana-3976 220 3 the the DET cana-3976 220 4 node node NOUN cana-3976 220 5 receives receive VERB cana-3976 220 6 fewer few ADJ cana-3976 220 7 rows row NOUN cana-3976 220 8 than than ADP cana-3976 220 9 a a DET cana-3976 220 10 specific specific ADJ cana-3976 220 11 limit limit NOUN cana-3976 220 12 . . PUNCT cana-3976 221 1 3 3 X cana-3976 221 2 . . X cana-3976 221 3 each each DET cana-3976 221 4 column column NOUN cana-3976 221 5 of of ADP cana-3976 221 6 data datum NOUN cana-3976 221 7 has have VERB cana-3976 221 8 only only ADV cana-3976 221 9 one one NUM cana-3976 221 10 distinct distinct ADJ cana-3976 221 11 value value NOUN cana-3976 221 12 . . PUNCT cana-3976 222 1 after after ADP cana-3976 222 2 a a DET cana-3976 222 3 stopping stop VERB cana-3976 222 4 state state NOUN cana-3976 222 5 , , PUNCT cana-3976 222 6 we we PRON cana-3976 222 7 returned return VERB cana-3976 222 8 the the DET cana-3976 222 9 probability probability NOUN cana-3976 222 10 distribution distribution NOUN cana-3976 222 11 and and CCONJ cana-3976 222 12 data datum NOUN cana-3976 222 13 set set VERB cana-3976 222 14 class class NOUN cana-3976 222 15 label label NOUN cana-3976 222 16 frequencies frequency NOUN cana-3976 222 17 . . PUNCT cana-3976 223 1 the the DET cana-3976 223 2 distribution distribution NOUN cana-3976 223 3 removes remove VERB cana-3976 223 4 outliers outlier NOUN cana-3976 223 5 . . PUNCT cana-3976 224 1 thus thus ADV cana-3976 224 2 , , PUNCT cana-3976 224 3 we we PRON cana-3976 224 4 may may AUX cana-3976 224 5 weigh weigh VERB cana-3976 224 6 each each DET cana-3976 224 7 ensemble ensemble ADJ cana-3976 224 8 tree tree NOUN cana-3976 224 9 's 's PART cana-3976 224 10 vote vote NOUN cana-3976 224 11 . . PUNCT cana-3976 225 1 repeat repeat VERB cana-3976 225 2 the the DET cana-3976 225 3 process process NOUN cana-3976 225 4 m m NOUN cana-3976 225 5 times time NOUN cana-3976 225 6 to to PART cana-3976 225 7 train train VERB cana-3976 225 8 m m NOUN cana-3976 225 9 trees tree NOUN cana-3976 225 10 . . PUNCT cana-3976 226 1 in in ADP cana-3976 226 2 " " PUNCT cana-3976 226 3 algorithm algorithm NOUN cana-3976 226 4 1 1 NUM cana-3976 226 5 , , PUNCT cana-3976 226 6 " " PUNCT cana-3976 226 7 we we PRON cana-3976 226 8 employ employ VERB cana-3976 226 9 a a DET cana-3976 226 10 high high ADJ cana-3976 226 11 - - PUNCT cana-3976 226 12 level level NOUN cana-3976 226 13 pseudo pseudo NOUN cana-3976 226 14 code code NOUN cana-3976 226 15 to to PART cana-3976 226 16 train train VERB cana-3976 226 17 a a DET cana-3976 226 18 single single ADJ cana-3976 226 19 dt dt NOUN cana-3976 226 20 . . PUNCT cana-3976 227 1 _ _ PUNCT cana-3976 228 1 _ _ PUNCT cana-3976 229 1 _ _ PUNCT cana-3976 230 1 _ _ PUNCT cana-3976 231 1 _ _ PUNCT cana-3976 232 1 _ _ PUNCT cana-3976 233 1 _ _ PUNCT cana-3976 234 1 _ _ PUNCT cana-3976 235 1 _ _ PUNCT cana-3976 236 1 _ _ PUNCT cana-3976 237 1 _ _ PUNCT cana-3976 238 1 _ _ PUNCT cana-3976 239 1 _ _ PUNCT cana-3976 240 1 _ _ PUNCT cana-3976 241 1 _ _ PUNCT cana-3976 242 1 _ _ PUNCT cana-3976 243 1 _ _ PUNCT cana-3976 244 1 _ _ PUNCT cana-3976 245 1 _ _ PUNCT cana-3976 246 1 _ _ PUNCT cana-3976 247 1 _ _ PUNCT cana-3976 248 1 _ _ PUNCT cana-3976 249 1 _ _ PUNCT cana-3976 250 1 _ _ PUNCT cana-3976 251 1 _ _ PUNCT cana-3976 252 1 _ _ PUNCT cana-3976 253 1 _ _ PUNCT cana-3976 254 1 _ _ PUNCT cana-3976 255 1 _ _ PUNCT cana-3976 256 1 _ _ PUNCT cana-3976 257 1 _ _ PUNCT cana-3976 258 1 _ _ PUNCT cana-3976 259 1 _ _ PUNCT cana-3976 260 1 _ _ PUNCT cana-3976 261 1 _ _ PUNCT cana-3976 262 1 _ _ PUNCT cana-3976 263 1 _ _ PUNCT cana-3976 264 1 _ _ PUNCT cana-3976 265 1 _ _ PUNCT cana-3976 266 1 _ _ PUNCT cana-3976 267 1 _ _ PUNCT cana-3976 268 1 _ _ PUNCT cana-3976 269 1 _ _ PUNCT cana-3976 270 1 _ _ PUNCT cana-3976 271 1 _ _ PUNCT cana-3976 272 1 _ _ PUNCT cana-3976 273 1 _ _ PUNCT cana-3976 274 1 _ _ PUNCT cana-3976 275 1 _ _ PUNCT cana-3976 276 1 _ _ PUNCT cana-3976 277 1 _ _ PUNCT cana-3976 277 2 algorithm algorithm NOUN cana-3976 277 3 1 1 NUM cana-3976 277 4 : : PUNCT cana-3976 277 5 procedure procedure NOUN cana-3976 277 6 of of ADP cana-3976 277 7 eta eta PROPN cana-3976 277 8 _ _ PUNCT cana-3976 278 1 _ _ PUNCT cana-3976 279 1 _ _ PUNCT cana-3976 280 1 _ _ PUNCT cana-3976 281 1 _ _ PUNCT cana-3976 282 1 _ _ PUNCT cana-3976 283 1 _ _ PUNCT cana-3976 284 1 _ _ PUNCT cana-3976 285 1 _ _ PUNCT cana-3976 286 1 _ _ PUNCT cana-3976 287 1 _ _ PUNCT cana-3976 288 1 _ _ PUNCT cana-3976 289 1 _ _ PUNCT cana-3976 290 1 _ _ PUNCT cana-3976 291 1 _ _ PUNCT cana-3976 292 1 _ _ PUNCT cana-3976 293 1 _ _ PUNCT cana-3976 294 1 _ _ PUNCT cana-3976 295 1 _ _ PUNCT cana-3976 296 1 _ _ PUNCT cana-3976 297 1 _ _ PUNCT cana-3976 298 1 _ _ PUNCT cana-3976 299 1 _ _ PUNCT cana-3976 300 1 _ _ PUNCT cana-3976 301 1 _ _ PUNCT cana-3976 302 1 _ _ PUNCT cana-3976 303 1 _ _ PUNCT cana-3976 304 1 _ _ PUNCT cana-3976 305 1 _ _ PUNCT cana-3976 306 1 _ _ PUNCT cana-3976 307 1 _ _ PUNCT cana-3976 308 1 _ _ PUNCT cana-3976 309 1 _ _ PUNCT cana-3976 310 1 _ _ PUNCT cana-3976 311 1 _ _ PUNCT cana-3976 312 1 _ _ PUNCT cana-3976 313 1 _ _ PUNCT cana-3976 314 1 _ _ PUNCT cana-3976 315 1 _ _ PUNCT cana-3976 316 1 _ _ PUNCT cana-3976 317 1 _ _ PUNCT cana-3976 318 1 _ _ PUNCT cana-3976 319 1 _ _ PUNCT cana-3976 320 1 _ _ PUNCT cana-3976 321 1 _ _ PUNCT cana-3976 322 1 _ _ PUNCT cana-3976 323 1 _ _ PUNCT cana-3976 324 1 _ _ PUNCT cana-3976 325 1 _ _ PUNCT cana-3976 326 1 _ _ PUNCT cana-3976 327 1 _ _ PUNCT cana-3976 328 1 _ _ PUNCT cana-3976 329 1 _ _ PUNCT cana-3976 330 1 _ _ PUNCT cana-3976 331 1 _ _ PUNCT cana-3976 332 1 _ _ PUNCT cana-3976 333 1 input input NOUN cana-3976 333 2 : : PUNCT cana-3976 333 3 training training NOUN cana-3976 333 4 set set VERB cana-3976 333 5 s. s. PROPN cana-3976 333 6 output output PROPN cana-3976 333 7 : : PUNCT cana-3976 333 8 e e X cana-3976 333 9 = = SYM cana-3976 333 10 t1 t1 PROPN cana-3976 333 11 , , PUNCT cana-3976 333 12 ... ... PUNCT cana-3976 333 13 , , PUNCT cana-3976 333 14 tm tm PROPN cana-3976 333 15 1 1 NUM cana-3976 333 16 function function NOUN cana-3976 333 17 construct construct NOUN cana-3976 333 18 required require VERB cana-3976 333 19 no.of no.of PROPN cana-3976 333 20 trees tree NOUN cana-3976 333 21 ( ( PUNCT cana-3976 333 22 s s X cana-3976 333 23 , , PUNCT cana-3976 333 24 k k PROPN cana-3976 333 25 , , PUNCT cana-3976 333 26 m m PROPN cana-3976 333 27 , , PUNCT cana-3976 333 28 n n CCONJ cana-3976 333 29 ) ) PUNCT cana-3976 333 30 2 2 NUM cana-3976 333 31 if if SCONJ cana-3976 333 32 |s| |s| NOUN cana-3976 333 33 โ‰ค โ‰ค NOUN cana-3976 333 34 n n ADP cana-3976 333 35 or or CCONJ cana-3976 333 36 all all DET cana-3976 333 37 classes class NOUN cana-3976 333 38 in in ADP cana-3976 333 39 s s NOUN cana-3976 333 40 are be AUX cana-3976 333 41 constant constant ADJ cana-3976 333 42 then then ADV cana-3976 333 43 3 3 NUM cana-3976 333 44 return return NOUN cana-3976 333 45 class class NOUN cana-3976 333 46 frequencies frequency NOUN cana-3976 333 47 4 4 NUM cana-3976 333 48 else else ADV cana-3976 333 49 communications communication NOUN cana-3976 333 50 on on ADP cana-3976 333 51 applied apply VERB cana-3976 333 52 nonlinear nonlinear ADJ cana-3976 333 53 analysis analysis NOUN cana-3976 333 54 issn issn NOUN cana-3976 333 55 : : PUNCT cana-3976 333 56 1074 1074 NUM cana-3976 333 57 - - PUNCT cana-3976 333 58 133x 133x NUM cana-3976 333 59 vol vol NOUN cana-3976 333 60 32 32 NUM cana-3976 333 61 no no NOUN cana-3976 333 62 . . PUNCT cana-3976 334 1 9s 9s NUM cana-3976 334 2 ( ( PUNCT cana-3976 334 3 2025 2025 NUM cana-3976 334 4 ) ) PUNCT cana-3976 334 5 712 712 NUM cana-3976 334 6 https://internationalpubls.com https://internationalpubls.com X cana-3976 334 7 5 5 NUM cana-3976 334 8 a a DET cana-3976 334 9 random random ADJ cana-3976 334 10 selection selection NOUN cana-3976 334 11 of of ADP cana-3976 334 12 k k PROPN cana-3976 334 13 ( ( PUNCT cana-3976 334 14 non non ADJ cana-3976 334 15 - - ADJ cana-3976 334 16 constant constant ADJ cana-3976 334 17 valued value VERB cana-3976 334 18 ) ) PUNCT cana-3976 334 19 attributes attribute VERB cana-3976 334 20 , , PUNCT cana-3976 334 21 { { PUNCT cana-3976 334 22 a1 a1 NOUN cana-3976 334 23 , , PUNCT cana-3976 334 24 ... ... PUNCT cana-3976 334 25 , , PUNCT cana-3976 334 26 ak ak PROPN cana-3976 334 27 } } PUNCT cana-3976 334 28 , , PUNCT cana-3976 334 29 from from ADP cana-3976 334 30 all all PRON cana-3976 334 31 of of ADP cana-3976 334 32 the the DET cana-3976 334 33 candidate candidate NOUN cana-3976 334 34 attributes attribute VERB cana-3976 334 35 in in ADP cana-3976 334 36 s s NOUN cana-3976 334 37 is be AUX cana-3976 334 38 to to PART cana-3976 334 39 be be AUX cana-3976 334 40 made make VERB cana-3976 334 41 without without ADP cana-3976 334 42 replacement replacement NOUN cana-3976 334 43 . . PUNCT cana-3976 335 1 6 6 NUM cana-3976 335 2 producek producek NOUN cana-3976 335 3 splits split VERB cana-3976 335 4 , , PUNCT cana-3976 335 5 { { PUNCT cana-3976 335 6 s1 s1 NOUN cana-3976 335 7 , , PUNCT cana-3976 335 8 ... ... PUNCT cana-3976 335 9 , , PUNCT cana-3976 335 10 sk sk SCONJ cana-3976 335 11 } } PUNCT cana-3976 335 12 7 7 NUM cana-3976 335 13 choose choose NOUN cana-3976 335 14 s s NOUN cana-3976 335 15 ' ' PUNCT cana-3976 335 16 so so SCONJ cana-3976 335 17 that that SCONJ cana-3976 335 18 it it PRON cana-3976 335 19 fulfils fulfil VERB cana-3976 335 20 the the DET cana-3976 335 21 following follow VERB cana-3976 335 22 equation equation NOUN cana-3976 335 23 : : PUNCT cana-3976 335 24 score(s score(s NOUN cana-3976 335 25 ' ' PUNCT cana-3976 335 26 , , PUNCT cana-3976 335 27 s s X cana-3976 335 28 ) ) PUNCT cana-3976 335 29 = = SYM cana-3976 335 30 maxi1, maxi1, PROPN cana-3976 335 31 ... ... PUNCT cana-3976 335 32 ,k ,k PUNCT cana-3976 335 33 score(si score(si PROPN cana-3976 335 34 , , PUNCT cana-3976 335 35 s s PART cana-3976 335 36 ) ) PUNCT cana-3976 335 37 , , PUNCT cana-3976 335 38 8 8 NUM cana-3976 335 39 from from ADP cana-3976 335 40 s s PROPN cana-3976 335 41 โ€™ ' PUNCT cana-3976 335 42 , , PUNCT cana-3976 335 43 split split VERB cana-3976 335 44 s s PART cana-3976 335 45 9 9 NUM cana-3976 335 46 considertl= considertl= NUM cana-3976 335 47 construct construct VERB cana-3976 335 48 extra extra ADJ cana-3976 335 49 tree(sl tree(sl NOUN cana-3976 335 50 ) ) PUNCT cana-3976 335 51 and and CCONJ cana-3976 335 52 tr= tr= PROPN cana-3976 335 53 ( ( PUNCT cana-3976 335 54 sr sr PROPN cana-3976 335 55 ) ) PUNCT cana-3976 335 56 10 10 NUM cana-3976 335 57 generate generate VERB cana-3976 335 58 a a DET cana-3976 335 59 node node NOUN cana-3976 335 60 n n NOUN cana-3976 335 61 with with ADP cana-3976 335 62 the the DET cana-3976 335 63 split split NOUN cana-3976 335 64 s s NOUN cana-3976 335 65 โ€™ ' PUNCT cana-3976 335 66 11 11 NUM cana-3976 335 67 end end NOUN cana-3976 335 68 12 12 NUM cana-3976 335 69 return return NOUN cana-3976 335 70 n n DET cana-3976 335 71 4 4 NUM cana-3976 335 72 . . PUNCT cana-3976 336 1 results result NOUN cana-3976 336 2 and and CCONJ cana-3976 336 3 discussion discussion NOUN cana-3976 337 1 : : PUNCT cana-3976 337 2 in in ADP cana-3976 337 3 this this DET cana-3976 337 4 case case NOUN cana-3976 337 5 , , PUNCT cana-3976 337 6 we we PRON cana-3976 337 7 resolved resolve VERB cana-3976 337 8 every every DET cana-3976 337 9 classification classification NOUN cana-3976 337 10 issue issue NOUN cana-3976 337 11 using use VERB cana-3976 337 12 windows window NOUN cana-3976 337 13 10 10 NUM cana-3976 337 14 , , PUNCT cana-3976 337 15 python python NOUN cana-3976 337 16 3.6 3.6 NUM cana-3976 337 17 , , PUNCT cana-3976 337 18 and and CCONJ cana-3976 337 19 the the DET cana-3976 337 20 scikitlearn scikitlearn ADJ cana-3976 337 21 module module NOUN cana-3976 337 22 version version NOUN cana-3976 337 23 0.19.2 0.19.2 PROPN cana-3976 337 24 . . PUNCT cana-3976 338 1 we we PRON cana-3976 338 2 separated separate VERB cana-3976 338 3 participants participant NOUN cana-3976 338 4 in in ADP cana-3976 338 5 this this DET cana-3976 338 6 study study NOUN cana-3976 338 7 into into ADP cana-3976 338 8 two two NUM cana-3976 338 9 groups group NOUN cana-3976 338 10 : : PUNCT cana-3976 338 11 those those PRON cana-3976 338 12 who who PRON cana-3976 338 13 had have VERB cana-3976 338 14 dementia dementia NOUN cana-3976 338 15 and and CCONJ cana-3976 338 16 those those PRON cana-3976 338 17 who who PRON cana-3976 338 18 did do VERB cana-3976 338 19 not not PART cana-3976 338 20 . . PUNCT cana-3976 339 1 as as ADP cana-3976 339 2 a a DET cana-3976 339 3 result result NOUN cana-3976 339 4 , , PUNCT cana-3976 339 5 to to PART cana-3976 339 6 validate validate VERB cana-3976 339 7 our our PRON cana-3976 339 8 proposed propose VERB cana-3976 339 9 solution solution NOUN cana-3976 339 10 , , PUNCT cana-3976 339 11 we we PRON cana-3976 339 12 used use VERB cana-3976 339 13 anaconda anaconda PROPN cana-3976 339 14 for for ADP cana-3976 339 15 python python NOUN cana-3976 339 16 and and CCONJ cana-3976 339 17 tensorflow tensorflow NOUN cana-3976 339 18 on on ADP cana-3976 339 19 a a DET cana-3976 339 20 computer computer NOUN cana-3976 339 21 with with ADP cana-3976 339 22 8 8 NUM cana-3976 339 23 gigabytes gigabyte NOUN cana-3976 339 24 of of ADP cana-3976 339 25 random random ADJ cana-3976 339 26 access access NOUN cana-3976 339 27 memory memory NOUN cana-3976 339 28 and and CCONJ cana-3976 339 29 a a DET cana-3976 339 30 graphics graphics NOUN cana-3976 339 31 processing processing NOUN cana-3976 339 32 unit unit NOUN cana-3976 339 33 with with ADP cana-3976 339 34 intel intel PROPN cana-3976 339 35 hd hd PROPN cana-3976 339 36 6000 6000 NUM cana-3976 339 37 1536 1536 NUM cana-3976 339 38 megabytes megabyte NOUN cana-3976 339 39 . . PUNCT cana-3976 340 1 due due ADP cana-3976 340 2 to to ADP cana-3976 340 3 the the DET cana-3976 340 4 small small ADJ cana-3976 340 5 amount amount NOUN cana-3976 340 6 of of ADP cana-3976 340 7 the the DET cana-3976 340 8 dataset dataset NOUN cana-3976 340 9 , , PUNCT cana-3976 340 10 5 5 NUM cana-3976 340 11 - - ADJ cana-3976 340 12 fold fold ADJ cana-3976 340 13 cross cross NOUN cana-3976 340 14 - - ADJ cana-3976 340 15 validation validation NOUN cana-3976 340 16 is be AUX cana-3976 340 17 used use VERB cana-3976 340 18 . . PUNCT cana-3976 341 1 f1 f1 NOUN cana-3976 341 2 - - PUNCT cana-3976 341 3 score score NOUN cana-3976 341 4 is be AUX cana-3976 341 5 a a DET cana-3976 341 6 prominent prominent ADJ cana-3976 341 7 measure measure NOUN cana-3976 341 8 for for ADP cana-3976 341 9 assessing assess VERB cana-3976 341 10 the the DET cana-3976 341 11 precision precision NOUN cana-3976 341 12 of of ADP cana-3976 341 13 binary binary ADJ cana-3976 341 14 classification classification NOUN cana-3976 341 15 . . PUNCT cana-3976 342 1 the the DET cana-3976 342 2 score score NOUN cana-3976 342 3 is be AUX cana-3976 342 4 calculated calculate VERB cana-3976 342 5 using use VERB cana-3976 342 6 both both CCONJ cana-3976 342 7 recall recall NOUN cana-3976 342 8 and and CCONJ cana-3976 342 9 precision precision NOUN cana-3976 342 10 . . PUNCT cana-3976 343 1 when when SCONJ cana-3976 343 2 computing computing NOUN cana-3976 343 3 recall recall NOUN cana-3976 343 4 , , PUNCT cana-3976 343 5 the the DET cana-3976 343 6 denominator denominator NOUN cana-3976 343 7 includes include VERB cana-3976 343 8 all all DET cana-3976 343 9 similar similar ADJ cana-3976 343 10 samples sample NOUN cana-3976 343 11 that that PRON cana-3976 343 12 must must AUX cana-3976 343 13 be be AUX cana-3976 343 14 true true ADJ cana-3976 343 15 , , PUNCT cana-3976 343 16 while while SCONJ cana-3976 343 17 the the DET cana-3976 343 18 numerator numerator NOUN cana-3976 343 19 includes include VERB cana-3976 343 20 the the DET cana-3976 343 21 total total ADJ cana-3976 343 22 number number NOUN cana-3976 343 23 of of ADP cana-3976 343 24 correct correct ADJ cana-3976 343 25 , , PUNCT cana-3976 343 26 true true ADJ cana-3976 343 27 outputs output NOUN cana-3976 343 28 . . PUNCT cana-3976 344 1 furthermore furthermore ADV cana-3976 344 2 , , PUNCT cana-3976 344 3 the the DET cana-3976 344 4 precision precision NOUN cana-3976 344 5 is be AUX cana-3976 344 6 calculated calculate VERB cana-3976 344 7 by by ADP cana-3976 344 8 dividing divide VERB cana-3976 344 9 the the DET cana-3976 344 10 total total ADJ cana-3976 344 11 number number NOUN cana-3976 344 12 of of ADP cana-3976 344 13 correct correct ADJ cana-3976 344 14 outcomes outcome NOUN cana-3976 344 15 by by ADP cana-3976 344 16 the the DET cana-3976 344 17 number number NOUN cana-3976 344 18 of of ADP cana-3976 344 19 correct correct ADJ cana-3976 344 20 results result NOUN cana-3976 344 21 produced produce VERB cana-3976 344 22 by by ADP cana-3976 344 23 the the DET cana-3976 344 24 classifier classifier NOUN cana-3976 344 25 . . PUNCT cana-3976 345 1 the the DET cana-3976 345 2 f1 f1 NOUN cana-3976 345 3 - - PUNCT cana-3976 345 4 score score NOUN cana-3976 345 5 should should AUX cana-3976 345 6 be be AUX cana-3976 345 7 set set VERB cana-3976 345 8 to to ADP cana-3976 345 9 1 1 NUM cana-3976 345 10 for for ADP cana-3976 345 11 the the DET cana-3976 345 12 best good ADJ cana-3976 345 13 potential potential ADJ cana-3976 345 14 results result NOUN cana-3976 345 15 , , PUNCT cana-3976 345 16 according accord VERB cana-3976 345 17 to to ADP cana-3976 345 18 equation equation NOUN cana-3976 345 19 ( ( PUNCT cana-3976 345 20 9 9 NUM cana-3976 345 21 ) ) PUNCT cana-3976 345 22 . . PUNCT cana-3976 346 1 ๐น1 ๐น1 PROPN cana-3976 346 2 โˆ’ โˆ’ PROPN cana-3976 346 3 ๐‘ ๐‘๐‘œ๐‘Ÿ๐‘’ ๐‘ ๐‘๐‘œ๐‘Ÿ๐‘’ NOUN cana-3976 346 4 = = SYM cana-3976 346 5 ๐‘…๐‘’๐‘๐‘Ž๐‘™๐‘™ ๐‘…๐‘’๐‘๐‘Ž๐‘™๐‘™ PROPN cana-3976 346 6 ร— ร— PROPN cana-3976 346 7 ๐‘ƒ๐‘Ÿ๐‘’๐‘๐‘–๐‘ ๐‘–๐‘œ๐‘› ๐‘ƒ๐‘Ÿ๐‘’๐‘๐‘–๐‘ ๐‘–๐‘œ๐‘› PROPN cana-3976 346 8 ๐‘ƒ๐‘Ÿ๐‘’๐‘๐‘–๐‘ ๐‘–๐‘œ๐‘› ๐‘ƒ๐‘Ÿ๐‘’๐‘๐‘–๐‘ ๐‘–๐‘œ๐‘› PROPN cana-3976 346 9 + + CCONJ cana-3976 346 10 ๐‘…๐‘’๐‘๐‘Ž๐‘™๐‘™ ๐‘…๐‘’๐‘๐‘Ž๐‘™๐‘™ PROPN cana-3976 346 11 ร— ร— NOUN cana-3976 346 12 2 2 NUM cana-3976 346 13 ( ( PUNCT cana-3976 346 14 9 9 NUM cana-3976 346 15 ) ) PUNCT cana-3976 346 16 precision precision NOUN cana-3976 346 17 : : PUNCT cana-3976 346 18 because because SCONJ cana-3976 346 19 we we PRON cana-3976 346 20 want want VERB cana-3976 346 21 to to PART cana-3976 346 22 have have VERB cana-3976 346 23 faith faith NOUN cana-3976 346 24 in in ADP cana-3976 346 25 our our PRON cana-3976 346 26 forecast forecast NOUN cana-3976 346 27 , , PUNCT cana-3976 346 28 accuracy accuracy NOUN cana-3976 346 29 is be AUX cana-3976 346 30 highly highly ADV cana-3976 346 31 useful useful ADJ cana-3976 346 32 because because SCONJ cana-3976 346 33 it it PRON cana-3976 346 34 shows show VERB cana-3976 346 35 us we PRON cana-3976 346 36 what what DET cana-3976 346 37 proportion proportion NOUN cana-3976 346 38 of of ADP cana-3976 346 39 the the DET cana-3976 346 40 values value NOUN cana-3976 346 41 expected expect VERB cana-3976 346 42 to to PART cana-3976 346 43 be be AUX cana-3976 346 44 positive positive ADJ cana-3976 346 45 were be AUX cana-3976 346 46 positive positive ADJ cana-3976 346 47 , , PUNCT cana-3976 346 48 as as SCONJ cana-3976 346 49 shown show VERB cana-3976 346 50 by by ADP cana-3976 346 51 equation equation NOUN cana-3976 346 52 ( ( PUNCT cana-3976 346 53 10 10 NUM cana-3976 346 54 ) ) PUNCT cana-3976 346 55 . . PUNCT cana-3976 347 1 ๐‘ƒ๐‘Ÿ๐‘’๐‘๐‘–๐‘ ๐‘–๐‘œ๐‘› ๐‘ƒ๐‘Ÿ๐‘’๐‘๐‘–๐‘ ๐‘–๐‘œ๐‘› PROPN cana-3976 347 2 = = SYM cana-3976 347 3 ๐‘‡๐‘ƒ ๐‘‡๐‘ƒ PROPN cana-3976 347 4 ๐‘‡๐‘ƒ ๐‘‡๐‘ƒ PROPN cana-3976 347 5 + + CCONJ cana-3976 347 6 ๐น๐‘ƒ ๐น๐‘ƒ PROPN cana-3976 347 7 ( ( PUNCT cana-3976 347 8 10 10 NUM cana-3976 347 9 ) ) PUNCT cana-3976 347 10 recall recall NOUN cana-3976 347 11 : : PUNCT cana-3976 347 12 t t PROPN cana-3976 347 13 is be AUX cana-3976 347 14 also also ADV cana-3976 347 15 used use VERB cana-3976 347 16 in in ADP cana-3976 347 17 binary binary ADJ cana-3976 347 18 classification classification NOUN cana-3976 347 19 to to PART cana-3976 347 20 validate validate VERB cana-3976 347 21 the the DET cana-3976 347 22 positive positive ADJ cana-3976 347 23 examples example NOUN cana-3976 347 24 found find VERB cana-3976 347 25 . . PUNCT cana-3976 348 1 the the DET cana-3976 348 2 true true ADJ cana-3976 348 3 positive positive ADJ cana-3976 348 4 rate rate NOUN cana-3976 348 5 , , PUNCT cana-3976 348 6 also also ADV cana-3976 348 7 called call VERB cana-3976 348 8 recall recall NOUN cana-3976 348 9 , , PUNCT cana-3976 348 10 is be AUX cana-3976 348 11 used use VERB cana-3976 348 12 to to PART cana-3976 348 13 represent represent VERB cana-3976 348 14 the the DET cana-3976 348 15 percentage percentage NOUN cana-3976 348 16 of of ADP cana-3976 348 17 people people NOUN cana-3976 348 18 who who PRON cana-3976 348 19 are be AUX cana-3976 348 20 infected infect VERB cana-3976 348 21 with with ADP cana-3976 348 22 a a DET cana-3976 348 23 disease disease NOUN cana-3976 348 24 . . PUNCT cana-3976 349 1 equation equation NOUN cana-3976 349 2 ( ( PUNCT cana-3976 349 3 11 11 NUM cana-3976 349 4 ) ) PUNCT cana-3976 349 5 can can AUX cana-3976 349 6 be be AUX cana-3976 349 7 used use VERB cana-3976 349 8 to to PART cana-3976 349 9 determine determine VERB cana-3976 349 10 the the DET cana-3976 349 11 recall recall NOUN cana-3976 349 12 percentage percentage NOUN cana-3976 349 13 . . PUNCT cana-3976 350 1 ๐‘…๐‘’๐‘๐‘Ž๐‘™๐‘™ ๐‘…๐‘’๐‘๐‘Ž๐‘™๐‘™ PROPN cana-3976 350 2 = = SYM cana-3976 350 3 ๐‘‡๐‘ƒ ๐‘‡๐‘ƒ PROPN cana-3976 350 4 ๐‘‡๐‘ƒ ๐‘‡๐‘ƒ PROPN cana-3976 350 5 + + CCONJ cana-3976 350 6 ๐น๐‘ ๐น๐‘ PROPN cana-3976 350 7 ( ( PUNCT cana-3976 350 8 11 11 NUM cana-3976 350 9 ) ) PUNCT cana-3976 350 10 accuracy accuracy NOUN cana-3976 350 11 : : PUNCT cana-3976 350 12 the the DET cana-3976 350 13 term term NOUN cana-3976 350 14 accuracy accuracy NOUN cana-3976 350 15 can can AUX cana-3976 350 16 be be AUX cana-3976 350 17 used use VERB cana-3976 350 18 to to PART cana-3976 350 19 calculate calculate VERB cana-3976 350 20 the the DET cana-3976 350 21 proportion proportion NOUN cana-3976 350 22 of of ADP cana-3976 350 23 correct correct ADJ cana-3976 350 24 classification classification NOUN cana-3976 350 25 of of ADP cana-3976 350 26 all all DET cana-3976 350 27 observations observation NOUN cana-3976 350 28 . . PUNCT cana-3976 351 1 to to PART cana-3976 351 2 establish establish VERB cana-3976 351 3 the the DET cana-3976 351 4 precision precision NOUN cana-3976 351 5 , , PUNCT cana-3976 351 6 equation equation NOUN cana-3976 351 7 ( ( PUNCT cana-3976 351 8 12 12 NUM cana-3976 351 9 ) ) PUNCT cana-3976 351 10 is be AUX cana-3976 351 11 used use VERB cana-3976 351 12 . . PUNCT cana-3976 352 1 communications communication NOUN cana-3976 352 2 on on ADP cana-3976 352 3 applied apply VERB cana-3976 352 4 nonlinear nonlinear ADJ cana-3976 352 5 analysis analysis NOUN cana-3976 352 6 issn issn NOUN cana-3976 352 7 : : PUNCT cana-3976 352 8 1074 1074 NUM cana-3976 352 9 - - PUNCT cana-3976 352 10 133x 133x NUM cana-3976 352 11 vol vol NOUN cana-3976 352 12 32 32 NUM cana-3976 352 13 no no NOUN cana-3976 352 14 . . PUNCT cana-3976 353 1 9s 9s NUM cana-3976 353 2 ( ( PUNCT cana-3976 353 3 2025 2025 NUM cana-3976 353 4 ) ) PUNCT cana-3976 353 5 713 713 NUM cana-3976 354 1 https://internationalpubls.com https://internationalpubls.com X cana-3976 354 2 ๐ด๐‘๐‘๐‘ข๐‘Ÿ๐‘Ž๐‘๐‘ฆ ๐ด๐‘๐‘๐‘ข๐‘Ÿ๐‘Ž๐‘๐‘ฆ PROPN cana-3976 354 3 = = SYM cana-3976 354 4 ๐‘‡๐‘ƒ ๐‘‡๐‘ƒ PROPN cana-3976 354 5 + + CCONJ cana-3976 354 6 ๐‘‡๐‘ ๐‘‡๐‘ PROPN cana-3976 354 7 ๐‘‡๐‘ƒ ๐‘‡๐‘ƒ PROPN cana-3976 354 8 + + CCONJ cana-3976 354 9 ๐น๐‘ƒ ๐น๐‘ƒ PROPN cana-3976 354 10 + + CCONJ cana-3976 354 11 ๐‘‡๐‘ ๐‘‡๐‘ PROPN cana-3976 354 12 + + X cana-3976 354 13 ๐น๐‘ ๐น๐‘ PROPN cana-3976 354 14 ( ( PUNCT cana-3976 354 15 12 12 NUM cana-3976 354 16 ) ) PUNCT cana-3976 354 17 the the DET cana-3976 354 18 words word NOUN cana-3976 354 19 true true ADJ cana-3976 354 20 positive positive ADJ cana-3976 354 21 ( ( PUNCT cana-3976 354 22 tp tp NOUN cana-3976 354 23 ) ) PUNCT cana-3976 354 24 , , PUNCT cana-3976 354 25 false false ADJ cana-3976 354 26 positive positive ADJ cana-3976 354 27 ( ( PUNCT cana-3976 354 28 fp fp NOUN cana-3976 354 29 ) ) PUNCT cana-3976 354 30 , , PUNCT cana-3976 354 31 true true ADJ cana-3976 354 32 negative negative ADJ cana-3976 354 33 ( ( PUNCT cana-3976 354 34 tn tn NOUN cana-3976 354 35 ) ) PUNCT cana-3976 354 36 , , PUNCT cana-3976 354 37 and and CCONJ cana-3976 354 38 false false ADJ cana-3976 354 39 negative negative ADJ cana-3976 354 40 ( ( PUNCT cana-3976 354 41 fn fn NOUN cana-3976 354 42 ) ) PUNCT cana-3976 354 43 have have AUX cana-3976 354 44 been be AUX cana-3976 354 45 used use VERB cana-3976 354 46 to to PART cana-3976 354 47 refer refer VERB cana-3976 354 48 to to ADP cana-3976 354 49 symbols symbol NOUN cana-3976 354 50 in in ADP cana-3976 354 51 the the DET cana-3976 354 52 equations equation NOUN cana-3976 354 53 presented present VERB cana-3976 354 54 . . PUNCT cana-3976 355 1 figure3 figure3 NOUN cana-3976 355 2 : : PUNCT cana-3976 356 1 count count NOUN cana-3976 356 2 of of ADP cana-3976 356 3 patient patient NOUN cana-3976 356 4 i i PROPN cana-3976 356 5 d d PROPN cana-3976 356 6 table table NOUN cana-3976 356 7 3 3 NUM cana-3976 356 8 : : PUNCT cana-3976 356 9 classification classification NOUN cana-3976 356 10 for for ADP cana-3976 356 11 each each DET cana-3976 356 12 method method NOUN cana-3976 356 13 in in ADP cana-3976 356 14 minority minority NOUN cana-3976 356 15 class class NOUN cana-3976 356 16 for for ADP cana-3976 356 17 accuracy accuracy NOUN cana-3976 356 18 , , PUNCT cana-3976 356 19 precision precision NOUN cana-3976 356 20 , , PUNCT cana-3976 356 21 recall recall NOUN cana-3976 356 22 , , PUNCT cana-3976 356 23 and and CCONJ cana-3976 356 24 f1 f1 ADJ cana-3976 356 25 - - PUNCT cana-3976 356 26 score score NOUN cana-3976 356 27 model model NOUN cana-3976 356 28 accuracy accuracy NOUN cana-3976 356 29 precision precision NOUN cana-3976 356 30 recall recall VERB cana-3976 356 31 f1 f1 NOUN cana-3976 356 32 - - PUNCT cana-3976 356 33 score score NOUN cana-3976 356 34 svm svm NOUN cana-3976 356 35 0.78 0.78 NUM cana-3976 356 36 0.87 0.87 NUM cana-3976 356 37 0.68 0.68 NUM cana-3976 356 38 0.77 0.77 NUM cana-3976 356 39 dt dt NOUN cana-3976 356 40 0.79 0.79 NUM cana-3976 356 41 0.84 0.84 NUM cana-3976 356 42 0.77 0.77 NUM cana-3976 356 43 0.80 0.80 NUM cana-3976 356 44 gb gb ADP cana-3976 356 45 0.84 0.84 NUM cana-3976 356 46 0.86 0.86 NUM cana-3976 356 47 0.83 0.83 NUM cana-3976 356 48 0.85 0.85 NUM cana-3976 356 49 proposed propose VERB cana-3976 356 50 eta eta PROPN cana-3976 356 51 0.88 0.88 NUM cana-3976 356 52 0.93 0.93 NUM cana-3976 356 53 0.85 0.85 NUM cana-3976 356 54 0.89 0.89 NUM cana-3976 356 55 figure figure NOUN cana-3976 356 56 4 4 NUM cana-3976 356 57 depicts depict VERB cana-3976 356 58 the the DET cana-3976 356 59 image image NOUN cana-3976 356 60 classifier classifier NOUN cana-3976 356 61 's 's PART cana-3976 356 62 performance performance NOUN cana-3976 356 63 evaluation evaluation NOUN cana-3976 356 64 . . PUNCT cana-3976 357 1 we we PRON cana-3976 357 2 evaluated evaluate VERB cana-3976 357 3 the the DET cana-3976 357 4 performance performance NOUN cana-3976 357 5 using use VERB cana-3976 357 6 a a DET cana-3976 357 7 variety variety NOUN cana-3976 357 8 of of ADP cana-3976 357 9 algorithms algorithm NOUN cana-3976 357 10 . . PUNCT cana-3976 358 1 the the DET cana-3976 358 2 four four NUM cana-3976 358 3 algorithms algorithm NOUN cana-3976 358 4 studied study VERB cana-3976 358 5 and and CCONJ cana-3976 358 6 compared compare VERB cana-3976 358 7 were be AUX cana-3976 358 8 svm svm ADJ cana-3976 358 9 , , PUNCT cana-3976 358 10 dt dt NOUN cana-3976 358 11 , , PUNCT cana-3976 358 12 gb gb NOUN cana-3976 358 13 , , PUNCT cana-3976 358 14 and and CCONJ cana-3976 359 1 eta eta PROPN cana-3976 359 2 . . PUNCT cana-3976 359 3 communications communication NOUN cana-3976 359 4 on on ADP cana-3976 359 5 applied apply VERB cana-3976 359 6 nonlinear nonlinear ADJ cana-3976 359 7 analysis analysis NOUN cana-3976 359 8 issn issn NOUN cana-3976 359 9 : : PUNCT cana-3976 359 10 1074 1074 NUM cana-3976 359 11 - - PUNCT cana-3976 359 12 133x 133x NUM cana-3976 359 13 vol vol NOUN cana-3976 359 14 32 32 NUM cana-3976 359 15 no no NOUN cana-3976 359 16 . . PUNCT cana-3976 360 1 9s 9s NUM cana-3976 360 2 ( ( PUNCT cana-3976 360 3 2025 2025 NUM cana-3976 360 4 ) ) PUNCT cana-3976 360 5 714 714 NUM cana-3976 361 1 https://internationalpubls.com https://internationalpubls.com X cana-3976 361 2 svm svm PROPN cana-3976 361 3 , , PUNCT cana-3976 361 4 dt dt PROPN cana-3976 361 5 , , PUNCT cana-3976 361 6 gb gb NOUN cana-3976 361 7 , , PUNCT cana-3976 361 8 and and CCONJ cana-3976 361 9 eta eta PROPN cana-3976 361 10 were be AUX cana-3976 361 11 found find VERB cana-3976 361 12 to to PART cana-3976 361 13 have have VERB cana-3976 361 14 accuracy accuracy NOUN cana-3976 361 15 values value NOUN cana-3976 361 16 of of ADP cana-3976 361 17 0.78 0.78 NUM cana-3976 361 18 , , PUNCT cana-3976 361 19 0.79 0.79 NUM cana-3976 361 20 , , PUNCT cana-3976 361 21 0.84 0.84 NUM cana-3976 361 22 , , PUNCT cana-3976 361 23 and and CCONJ cana-3976 361 24 0.88 0.88 NUM cana-3976 361 25 , , PUNCT cana-3976 361 26 respectively respectively ADV cana-3976 361 27 . . PUNCT cana-3976 362 1 precision precision NOUN cana-3976 362 2 levels level NOUN cana-3976 362 3 for for ADP cana-3976 362 4 eta eta PROPN cana-3976 362 5 range range NOUN cana-3976 362 6 from from ADP cana-3976 362 7 0.93 0.93 NUM cana-3976 362 8 to to ADP cana-3976 362 9 0.84 0.84 NUM cana-3976 362 10 , , PUNCT cana-3976 362 11 with with ADP cana-3976 362 12 0.93 0.93 NUM cana-3976 362 13 being be AUX cana-3976 362 14 the the DET cana-3976 362 15 highest high ADJ cana-3976 362 16 and and CCONJ cana-3976 362 17 0.84 0.84 NUM cana-3976 362 18 being be AUX cana-3976 362 19 the the DET cana-3976 362 20 lowest low ADJ cana-3976 362 21 for for ADP cana-3976 362 22 the the DET cana-3976 362 23 dt dt PROPN cana-3976 362 24 model model NOUN cana-3976 362 25 . . PUNCT cana-3976 363 1 the the DET cana-3976 363 2 eta eta PROPN cana-3976 363 3 model model NOUN cana-3976 363 4 has have VERB cana-3976 363 5 the the DET cana-3976 363 6 highest high ADJ cana-3976 363 7 potential potential ADJ cana-3976 363 8 recall recall NOUN cana-3976 363 9 value value NOUN cana-3976 363 10 of of ADP cana-3976 363 11 0.85 0.85 NUM cana-3976 363 12 , , PUNCT cana-3976 363 13 while while SCONJ cana-3976 363 14 the the DET cana-3976 363 15 dt dt PROPN cana-3976 363 16 model model NOUN cana-3976 363 17 has have VERB cana-3976 363 18 the the DET cana-3976 363 19 lowest low ADJ cana-3976 363 20 possible possible ADJ cana-3976 363 21 value value NOUN cana-3976 363 22 of of ADP cana-3976 363 23 0.77 0.77 NUM cana-3976 363 24 . . PUNCT cana-3976 364 1 for for ADP cana-3976 364 2 the the DET cana-3976 364 3 f1 f1 ADJ cana-3976 364 4 - - PUNCT cana-3976 364 5 score score NOUN cana-3976 364 6 analysis analysis NOUN cana-3976 364 7 , , PUNCT cana-3976 364 8 the the DET cana-3976 364 9 svm svm PROPN cana-3976 364 10 , , PUNCT cana-3976 364 11 dt dt NOUN cana-3976 364 12 , , PUNCT cana-3976 364 13 gb gb NOUN cana-3976 364 14 , , PUNCT cana-3976 364 15 and and CCONJ cana-3976 365 1 eta eta PROPN cana-3976 365 2 values value NOUN cana-3976 365 3 were be AUX cana-3976 365 4 0.77 0.77 NUM cana-3976 365 5 , , PUNCT cana-3976 365 6 0.80 0.80 NUM cana-3976 365 7 , , PUNCT cana-3976 365 8 0.85 0.85 NUM cana-3976 365 9 , , PUNCT cana-3976 365 10 and and CCONJ cana-3976 365 11 0.89 0.89 NUM cana-3976 365 12 , , PUNCT cana-3976 365 13 respectively respectively ADV cana-3976 365 14 . . PUNCT cana-3976 366 1 figure figure VERB cana-3976 366 2 4 4 NUM cana-3976 366 3 : : PUNCT cana-3976 366 4 performance performance NOUN cana-3976 366 5 comparison comparison NOUN cana-3976 366 6 of of ADP cana-3976 366 7 proposed propose VERB cana-3976 366 8 work work NOUN cana-3976 366 9 and and CCONJ cana-3976 366 10 state state NOUN cana-3976 366 11 - - PUNCT cana-3976 366 12 of of ADP cana-3976 366 13 - - PUNCT cana-3976 366 14 the the DET cana-3976 366 15 - - PUNCT cana-3976 366 16 methods method NOUN cana-3976 366 17 for for ADP cana-3976 366 18 four four NUM cana-3976 366 19 metrics metric NOUN cana-3976 366 20 when when SCONJ cana-3976 366 21 the the DET cana-3976 366 22 suggested suggest VERB cana-3976 366 23 model model NOUN cana-3976 366 24 is be AUX cana-3976 366 25 analysed analyse VERB cana-3976 366 26 based base VERB cana-3976 366 27 on on ADP cana-3976 366 28 accuracy accuracy NOUN cana-3976 366 29 and and CCONJ cana-3976 366 30 loss loss NOUN cana-3976 366 31 for for ADP cana-3976 366 32 number number NOUN cana-3976 366 33 of of ADP cana-3976 366 34 epochs epoch NOUN cana-3976 366 35 , , PUNCT cana-3976 366 36 the the DET cana-3976 366 37 accuracy accuracy NOUN cana-3976 366 38 improves improve VERB cana-3976 366 39 but but CCONJ cana-3976 366 40 the the DET cana-3976 366 41 loss loss NOUN cana-3976 366 42 improves improve VERB cana-3976 366 43 less less ADV cana-3976 366 44 as as SCONJ cana-3976 366 45 depicted depict VERB cana-3976 366 46 in in ADP cana-3976 366 47 figures figure NOUN cana-3976 366 48 5(a 5(a NUM cana-3976 366 49 ) ) PUNCT cana-3976 366 50 and and CCONJ cana-3976 366 51 5(b 5(b NUM cana-3976 366 52 ) ) PUNCT cana-3976 366 53 . . PUNCT cana-3976 367 1 ( ( PUNCT cana-3976 367 2 a a X cana-3976 367 3 ) ) PUNCT cana-3976 367 4 ( ( PUNCT cana-3976 367 5 b b X cana-3976 367 6 ) ) PUNCT cana-3976 367 7 figure figure NOUN cana-3976 367 8 5 5 NUM cana-3976 367 9 : : PUNCT cana-3976 367 10 training training NOUN cana-3976 367 11 and and CCONJ cana-3976 367 12 validation validation NOUN cana-3976 367 13 accuracy accuracy NOUN cana-3976 367 14 and and CCONJ cana-3976 367 15 loss loss NOUN cana-3976 367 16 for for ADP cana-3976 367 17 proposed propose VERB cana-3976 367 18 work work NOUN cana-3976 367 19 figure figure NOUN cana-3976 367 20 6 6 NUM cana-3976 367 21 is be AUX cana-3976 367 22 the the DET cana-3976 367 23 receiver receiver NOUN cana-3976 367 24 operating operate VERB cana-3976 367 25 characteristic characteristic NOUN cana-3976 367 26 ( ( PUNCT cana-3976 367 27 roc roc PROPN cana-3976 367 28 ) ) PUNCT cana-3976 367 29 curve curve NOUN cana-3976 367 30 that that PRON cana-3976 367 31 shows show VERB cana-3976 367 32 the the DET cana-3976 367 33 auc auc NOUN cana-3976 367 34 of of ADP cana-3976 367 35 our our PRON cana-3976 367 36 work work NOUN cana-3976 367 37 is be AUX cana-3976 367 38 0.99 0.99 NUM cana-3976 367 39 for for ADP cana-3976 367 40 all all PRON cana-3976 367 41 of of ADP cana-3976 367 42 the the DET cana-3976 367 43 5 5 NUM cana-3976 367 44 folds fold NOUN cana-3976 367 45 . . PUNCT cana-3976 368 1 0 0 NUM cana-3976 368 2 0.1 0.1 NUM cana-3976 368 3 0.2 0.2 NUM cana-3976 368 4 0.3 0.3 NUM cana-3976 368 5 0.4 0.4 NUM cana-3976 368 6 0.5 0.5 NUM cana-3976 368 7 0.6 0.6 NUM cana-3976 368 8 0.7 0.7 NUM cana-3976 368 9 0.8 0.8 NUM cana-3976 368 10 0.9 0.9 NUM cana-3976 368 11 1 1 NUM cana-3976 368 12 accuracy accuracy NOUN cana-3976 368 13 precision precision NOUN cana-3976 368 14 recall recall NOUN cana-3976 368 15 f1 f1 NOUN cana-3976 368 16 - - PUNCT cana-3976 368 17 score score NOUN cana-3976 369 1 p p NOUN cana-3976 369 2 er er INTJ cana-3976 369 3 fo fo INTJ cana-3976 369 4 rm rm PROPN cana-3976 369 5 an an DET cana-3976 369 6 ce ce PROPN cana-3976 369 7 l l PROPN cana-3976 369 8 ev ev PROPN cana-3976 369 9 el el PROPN cana-3976 369 10 metric metric PROPN cana-3976 369 11 svm svm PROPN cana-3976 369 12 dt dt PROPN cana-3976 369 13 gb gb PROPN cana-3976 369 14 proposed propose VERB cana-3976 369 15 eta eta PROPN cana-3976 369 16 communications communication NOUN cana-3976 369 17 on on ADP cana-3976 369 18 applied apply VERB cana-3976 369 19 nonlinear nonlinear ADJ cana-3976 369 20 analysis analysis NOUN cana-3976 369 21 issn issn NOUN cana-3976 369 22 : : PUNCT cana-3976 369 23 1074 1074 NUM cana-3976 369 24 - - PUNCT cana-3976 369 25 133x 133x NUM cana-3976 369 26 vol vol NOUN cana-3976 369 27 32 32 NUM cana-3976 369 28 no no NOUN cana-3976 369 29 . . PUNCT cana-3976 370 1 9s 9s NUM cana-3976 370 2 ( ( PUNCT cana-3976 370 3 2025 2025 NUM cana-3976 370 4 ) ) PUNCT cana-3976 371 1 715 715 NUM cana-3976 371 2 https://internationalpubls.com https://internationalpubls.com X cana-3976 371 3 figure figure NOUN cana-3976 371 4 6 6 NUM cana-3976 371 5 : : PUNCT cana-3976 371 6 auc auc NOUN cana-3976 371 7 curve curve NOUN cana-3976 371 8 for for ADP cana-3976 371 9 ml ml NOUN cana-3976 371 10 approaches approach NOUN cana-3976 371 11 conclusions conclusion NOUN cana-3976 371 12 : : PUNCT cana-3976 371 13 using use VERB cana-3976 371 14 machine machine NOUN cana-3976 371 15 learning learning NOUN cana-3976 371 16 and and CCONJ cana-3976 371 17 data datum NOUN cana-3976 371 18 mining mining NOUN cana-3976 371 19 techniques technique NOUN cana-3976 371 20 to to PART cana-3976 371 21 detect detect VERB cana-3976 371 22 and and CCONJ cana-3976 371 23 diagnose diagnose VERB cana-3976 371 24 a a DET cana-3976 371 25 wide wide ADJ cana-3976 371 26 range range NOUN cana-3976 371 27 of of ADP cana-3976 371 28 ailments ailment NOUN cana-3976 371 29 would would AUX cana-3976 371 30 greatly greatly ADV cana-3976 371 31 benefit benefit VERB cana-3976 371 32 medicine medicine NOUN cana-3976 371 33 and and CCONJ cana-3976 371 34 healthcare healthcare PROPN cana-3976 371 35 research research NOUN cana-3976 371 36 . . PUNCT cana-3976 372 1 the the DET cana-3976 372 2 most most ADV cana-3976 372 3 common common ADJ cana-3976 372 4 myth myth NOUN cana-3976 372 5 regarding regard VERB cana-3976 372 6 alzheimer alzheimer PROPN cana-3976 372 7 's 's PART cana-3976 372 8 disease disease NOUN cana-3976 372 9 is be AUX cana-3976 372 10 that that SCONJ cana-3976 372 11 it it PRON cana-3976 372 12 is be AUX cana-3976 372 13 a a DET cana-3976 372 14 degenerative degenerative ADJ cana-3976 372 15 disorder disorder NOUN cana-3976 372 16 that that PRON cana-3976 372 17 can can AUX cana-3976 372 18 not not PART cana-3976 372 19 be be AUX cana-3976 372 20 cured cure VERB cana-3976 372 21 and and CCONJ cana-3976 372 22 ultimately ultimately ADV cana-3976 372 23 results result VERB cana-3976 372 24 in in ADP cana-3976 372 25 neuronal neuronal ADJ cana-3976 372 26 cell cell NOUN cana-3976 372 27 death death NOUN cana-3976 372 28 . . PUNCT cana-3976 373 1 regarding regard VERB cana-3976 373 2 alzheimer alzheimer PROPN cana-3976 373 3 's 's PART cana-3976 373 4 disease disease NOUN cana-3976 373 5 categorization categorization NOUN cana-3976 373 6 , , PUNCT cana-3976 373 7 the the DET cana-3976 373 8 machine machine NOUN cana-3976 373 9 learning learning NOUN cana-3976 373 10 technique technique NOUN cana-3976 373 11 has have AUX cana-3976 373 12 seen see VERB cana-3976 373 13 tremendous tremendous ADJ cana-3976 373 14 success success NOUN cana-3976 373 15 in in ADP cana-3976 373 16 the the DET cana-3976 373 17 medical medical ADJ cana-3976 373 18 sector sector NOUN cana-3976 373 19 , , PUNCT cana-3976 373 20 and and CCONJ cana-3976 373 21 it it PRON cana-3976 373 22 does do AUX cana-3976 373 23 not not PART cana-3976 373 24 require require VERB cana-3976 373 25 any any DET cana-3976 373 26 handmade handmade ADJ cana-3976 373 27 feature feature NOUN cana-3976 373 28 extraction extraction NOUN cana-3976 373 29 strategy strategy NOUN cana-3976 373 30 to to PART cana-3976 373 31 accomplish accomplish VERB cana-3976 373 32 this this DET cana-3976 373 33 accomplishment accomplishment NOUN cana-3976 373 34 . . PUNCT cana-3976 374 1 we we PRON cana-3976 374 2 propose propose VERB cana-3976 374 3 smote smote NOUN cana-3976 374 4 - - PUNCT cana-3976 374 5 wenn wenn PROPN cana-3976 374 6 , , PUNCT cana-3976 374 7 a a DET cana-3976 374 8 hybrid hybrid ADJ cana-3976 374 9 resampling resample VERB cana-3976 374 10 strategy strategy NOUN cana-3976 374 11 , , PUNCT cana-3976 374 12 as as ADP cana-3976 374 13 a a DET cana-3976 374 14 solution solution NOUN cana-3976 374 15 to to ADP cana-3976 374 16 the the DET cana-3976 374 17 problem problem NOUN cana-3976 374 18 of of ADP cana-3976 374 19 restricted restricted ADJ cana-3976 374 20 sample sample NOUN cana-3976 374 21 sizes size NOUN cana-3976 374 22 resulting result VERB cana-3976 374 23 in in ADP cana-3976 374 24 imbalanced imbalanced ADJ cana-3976 374 25 data datum NOUN cana-3976 374 26 classification classification NOUN cana-3976 374 27 in in ADP cana-3976 374 28 this this DET cana-3976 374 29 study study NOUN cana-3976 374 30 . . PUNCT cana-3976 375 1 smote smote VERB cana-3976 375 2 - - PUNCT cana-3976 375 3 wenn wenn PROPN cana-3976 375 4 can can AUX cana-3976 375 5 save save VERB cana-3976 375 6 a a DET cana-3976 375 7 significant significant ADJ cana-3976 375 8 proportion proportion NOUN cana-3976 375 9 of of ADP cana-3976 375 10 both both CCONJ cana-3976 375 11 good good ADJ cana-3976 375 12 and and CCONJ cana-3976 375 13 bad bad ADJ cana-3976 375 14 examples example NOUN cana-3976 375 15 of of ADP cana-3976 375 16 safe safe ADJ cana-3976 375 17 behavior behavior NOUN cana-3976 375 18 . . PUNCT cana-3976 376 1 this this PRON cana-3976 376 2 exploits exploit VERB cana-3976 376 3 the the DET cana-3976 376 4 wenn wenn PROPN cana-3976 376 5 distance distance NOUN cana-3976 376 6 scalings scaling NOUN cana-3976 376 7 for for ADP cana-3976 376 8 positive positive ADJ cana-3976 376 9 and and CCONJ cana-3976 376 10 negative negative ADJ cana-3976 376 11 candidates candidate NOUN cana-3976 376 12 whose whose DET cana-3976 376 13 nearest near ADJ cana-3976 376 14 neighbors neighbor NOUN cana-3976 376 15 are be AUX cana-3976 376 16 different different ADJ cana-3976 376 17 . . PUNCT cana-3976 377 1 the the DET cana-3976 377 2 results result NOUN cana-3976 377 3 of of ADP cana-3976 377 4 the the DET cana-3976 377 5 experiments experiment NOUN cana-3976 377 6 reveal reveal VERB cana-3976 377 7 that that SCONJ cana-3976 377 8 the the DET cana-3976 377 9 proposed propose VERB cana-3976 377 10 designs design NOUN cana-3976 377 11 are be AUX cana-3976 377 12 appropriate appropriate ADJ cana-3976 377 13 examples example NOUN cana-3976 377 14 of of ADP cana-3976 377 15 basic basic ADJ cana-3976 377 16 structures structure NOUN cana-3976 377 17 that that PRON cana-3976 377 18 minimize minimize VERB cana-3976 377 19 the the DET cana-3976 377 20 complexity complexity NOUN cana-3976 377 21 of of ADP cana-3976 377 22 computational computational ADJ cana-3976 377 23 time time NOUN cana-3976 377 24 , , PUNCT cana-3976 377 25 memory memory NOUN cana-3976 377 26 requirements requirement NOUN cana-3976 377 27 , , PUNCT cana-3976 377 28 and and CCONJ cana-3976 377 29 overfitting overfitte VERB cana-3976 377 30 and and CCONJ cana-3976 377 31 provide provide VERB cana-3976 377 32 more more ADV cana-3976 377 33 efficient efficient ADJ cana-3976 377 34 time time NOUN cana-3976 377 35 . . PUNCT cana-3976 378 1 furthermore furthermore ADV cana-3976 378 2 , , PUNCT cana-3976 378 3 2d 2d NUM cana-3976 378 4 multi multi ADJ cana-3976 378 5 - - ADJ cana-3976 378 6 class class ADJ cana-3976 378 7 ad ad NOUN cana-3976 378 8 stage stage NOUN cana-3976 378 9 classifications classification NOUN cana-3976 378 10 reach reach VERB cana-3976 378 11 highly highly ADV cana-3976 378 12 promising promising ADJ cana-3976 378 13 accuracy accuracy NOUN cana-3976 378 14 levels level NOUN cana-3976 378 15 , , PUNCT cana-3976 378 16 93.61 93.61 NUM cana-3976 378 17 % % NOUN cana-3976 378 18 , , PUNCT cana-3976 378 19 and and CCONJ cana-3976 378 20 95.17 95.17 NUM cana-3976 378 21 % % NOUN cana-3976 378 22 , , PUNCT cana-3976 378 23 respectively respectively ADV cana-3976 378 24 . . PUNCT cana-3976 379 1 references reference NOUN cana-3976 379 2 : : PUNCT cana-3976 380 1 [ [ X cana-3976 380 2 1 1 NUM cana-3976 380 3 ] ] X cana-3976 380 4 mayeux mayeux PROPN cana-3976 380 5 , , PUNCT cana-3976 380 6 r. r. PROPN cana-3976 380 7 ; ; PUNCT cana-3976 380 8 sano sano PROPN cana-3976 380 9 , , PUNCT cana-3976 380 10 m. m. NOUN cana-3976 380 11 treatment treatment NOUN cana-3976 380 12 of of ADP cana-3976 380 13 alzheimer alzheimer PROPN cana-3976 380 14 โ€™s โ€™s PART cana-3976 380 15 disease disease NOUN cana-3976 380 16 . . PUNCT cana-3976 381 1 n. n. PROPN cana-3976 381 2 engl engl PROPN cana-3976 381 3 . . PUNCT cana-3976 382 1 j. j. PROPN cana-3976 382 2 med med PROPN cana-3976 382 3 . . PROPN cana-3976 382 4 1999 1999 NUM cana-3976 382 5 , , PUNCT cana-3976 382 6 341 341 NUM cana-3976 382 7 , , PUNCT cana-3976 382 8 1670โ€“1679 1670โ€“1679 NUM cana-3976 382 9 . . PUNCT cana-3976 383 1 [ [ X cana-3976 383 2 2 2 NUM cana-3976 383 3 ] ] SYM cana-3976 383 4 alzheimer alzheimer PROPN cana-3976 383 5 โ€™s โ€™s PROPN cana-3976 383 6 association association PROPN cana-3976 383 7 . . PUNCT cana-3976 384 1 facts fact NOUN cana-3976 384 2 and and CCONJ cana-3976 384 3 figures figure NOUN cana-3976 384 4 . . PUNCT cana-3976 385 1 available available ADJ cana-3976 385 2 online online ADV cana-3976 385 3 : : PUNCT cana-3976 386 1 https://www.alz.org/alzheimersdementia/ https://www.alz.org/alzheimersdementia/ NOUN cana-3976 386 2 facts fact NOUN cana-3976 386 3 - - PUNCT cana-3976 386 4 figures figure NOUN cana-3976 386 5 ( ( PUNCT cana-3976 386 6 accessed access VERB cana-3976 386 7 on on ADP cana-3976 386 8 15 15 NUM cana-3976 386 9 october october NOUN cana-3976 386 10 2018 2018 NUM cana-3976 386 11 ) ) PUNCT cana-3976 386 12 . . PUNCT cana-3976 387 1 [ [ X cana-3976 387 2 3 3 NUM cana-3976 387 3 ] ] SYM cana-3976 387 4 vanmeter vanmeter NOUN cana-3976 387 5 , , PUNCT cana-3976 387 6 k. k. PROPN cana-3976 387 7 ; ; PUNCT cana-3976 387 8 hubert hubert PROPN cana-3976 387 9 , , PUNCT cana-3976 387 10 r.j r.j PROPN cana-3976 387 11 . . PROPN cana-3976 387 12 gould gould PROPN cana-3976 387 13 โ€™s โ€™s PART cana-3976 387 14 pathophysiology pathophysiology NOUN cana-3976 387 15 for for ADP cana-3976 387 16 the the DET cana-3976 387 17 health health NOUN cana-3976 387 18 professions profession NOUN cana-3976 387 19 , , PUNCT cana-3976 387 20 6th 6th ADJ cana-3976 387 21 ed ed NOUN cana-3976 387 22 . . PUNCT cana-3976 387 23 ; ; PUNCT cana-3976 387 24 elsevier elsevier PROPN cana-3976 387 25 : : PUNCT cana-3976 387 26 st st PROPN cana-3976 387 27 . . PROPN cana-3976 387 28 louis louis PROPN cana-3976 387 29 , , PUNCT cana-3976 387 30 mo mo PROPN cana-3976 387 31 , , PUNCT cana-3976 387 32 usa usa PROPN cana-3976 387 33 , , PUNCT cana-3976 387 34 2017 2017 NUM cana-3976 387 35 . . PUNCT cana-3976 388 1 0 0 NUM cana-3976 388 2 0.1 0.1 NUM cana-3976 388 3 0.2 0.2 NUM cana-3976 388 4 0.3 0.3 NUM cana-3976 388 5 0.4 0.4 NUM cana-3976 388 6 0.5 0.5 NUM cana-3976 388 7 0.6 0.6 NUM cana-3976 388 8 0.7 0.7 NUM cana-3976 388 9 0.8 0.8 NUM cana-3976 388 10 0.9 0.9 NUM cana-3976 388 11 1 1 NUM cana-3976 388 12 0 0 NUM cana-3976 388 13 0.1 0.1 NUM cana-3976 388 14 0.2 0.2 NUM cana-3976 388 15 0.3 0.3 NUM cana-3976 388 16 0.4 0.4 NUM cana-3976 388 17 0.5 0.5 NUM cana-3976 388 18 0.6 0.6 NUM cana-3976 388 19 0.7 0.7 NUM cana-3976 388 20 0.8 0.8 NUM cana-3976 388 21 0.9 0.9 NUM cana-3976 388 22 1 1 NUM cana-3976 388 23 fpr fpr NOUN cana-3976 388 24 ) ) PUNCT cana-3976 388 25 t t NOUN cana-3976 388 26 p p NOUN cana-3976 388 27 r r NOUN cana-3976 388 28 svm svm NOUN cana-3976 388 29 ( ( PUNCT cana-3976 388 30 auc= auc= PROPN cana-3976 388 31 0.93 0.93 NUM cana-3976 388 32 ) ) PUNCT cana-3976 388 33 dt(auc= dt(auc= NOUN cana-3976 388 34 0.94 0.94 NUM cana-3976 388 35 gb(auc= gb(auc= NOUN cana-3976 388 36 0.97 0.97 NUM cana-3976 388 37 our our PRON cana-3976 388 38 work(auc= work(auc= PROPN cana-3976 388 39 0.99 0.99 NUM cana-3976 388 40 communications communication NOUN cana-3976 388 41 on on ADP cana-3976 388 42 applied apply VERB cana-3976 388 43 nonlinear nonlinear ADJ cana-3976 388 44 analysis analysis NOUN cana-3976 388 45 issn issn NOUN cana-3976 388 46 : : PUNCT cana-3976 388 47 1074 1074 NUM cana-3976 388 48 - - PUNCT cana-3976 388 49 133x 133x NUM cana-3976 388 50 vol vol NOUN cana-3976 388 51 32 32 NUM cana-3976 389 1 no no NOUN cana-3976 389 2 . . PUNCT cana-3976 390 1 9s 9s NUM cana-3976 390 2 ( ( PUNCT cana-3976 390 3 2025 2025 NUM cana-3976 390 4 ) ) PUNCT cana-3976 390 5 716 716 NUM cana-3976 390 6 https://internationalpubls.com https://internationalpubls.com X cana-3976 391 1 [ [ X cana-3976 391 2 4 4 NUM cana-3976 391 3 ] ] PUNCT cana-3976 391 4 a. a. NOUN cana-3976 391 5 krizhevsky krizhevsky PROPN cana-3976 391 6 , , PUNCT cana-3976 391 7 i. i. PROPN cana-3976 391 8 sutskever sutskever PROPN cana-3976 391 9 , , PUNCT cana-3976 391 10 and and CCONJ cana-3976 391 11 g. g. PROPN cana-3976 391 12 e. e. PROPN cana-3976 391 13 hinton hinton PROPN cana-3976 391 14 , , PUNCT cana-3976 391 15 imagenet imagenet NOUN cana-3976 391 16 classification classification NOUN cana-3976 391 17 with with ADP cana-3976 391 18 deep deep ADJ cana-3976 391 19 convolutional convolutional ADJ cana-3976 391 20 neural neural ADJ cana-3976 391 21 networks network NOUN cana-3976 391 22 ( ( PUNCT cana-3976 391 23 2012 2012 NUM cana-3976 391 24 ) ) PUNCT cana-3976 391 25 , , PUNCT cana-3976 391 26 advances advance NOUN cana-3976 391 27 in in ADP cana-3976 391 28 neural neural ADJ cana-3976 391 29 information information NOUN cana-3976 391 30 processing processing NOUN cana-3976 391 31 systems system NOUN cana-3976 391 32 , , PUNCT cana-3976 391 33 p. p. NOUN cana-3976 391 34 1097 1097 NUM cana-3976 391 35 - - SYM cana-3976 391 36 1105 1105 NUM cana-3976 391 37 . . PUNCT cana-3976 392 1 [ [ X cana-3976 392 2 5 5 X cana-3976 392 3 ] ] PUNCT cana-3976 392 4 h. h. PROPN cana-3976 392 5 greenspan greenspan PROPN cana-3976 392 6 , , PUNCT cana-3976 392 7 b. b. PROPN cana-3976 392 8 van van PROPN cana-3976 392 9 ginneken ginneken PROPN cana-3976 392 10 , , PUNCT cana-3976 392 11 and and CCONJ cana-3976 392 12 r. r. PROPN cana-3976 392 13 m. m. PROPN cana-3976 392 14 summers summer NOUN cana-3976 392 15 , , PUNCT cana-3976 392 16 guest guest NOUN cana-3976 392 17 editorial editorial NOUN cana-3976 392 18 deep deep ADJ cana-3976 392 19 learning learning NOUN cana-3976 392 20 in in ADP cana-3976 392 21 medical medical ADJ cana-3976 392 22 imaging imaging NOUN cana-3976 392 23 : : PUNCT cana-3976 392 24 overview overview NOUN cana-3976 392 25 and and CCONJ cana-3976 392 26 future future ADJ cana-3976 392 27 promise promise NOUN cana-3976 392 28 of of ADP cana-3976 392 29 an an DET cana-3976 392 30 exciting exciting ADJ cana-3976 392 31 new new ADJ cana-3976 392 32 technique technique NOUN cana-3976 392 33 ( ( PUNCT cana-3976 392 34 2016 2016 NUM cana-3976 392 35 ) ) PUNCT cana-3976 392 36 , , PUNCT cana-3976 392 37 ieee ieee NOUN cana-3976 392 38 transactions transaction NOUN cana-3976 392 39 on on ADP cana-3976 392 40 medical medical ADJ cana-3976 392 41 imaging imaging NOUN cana-3976 392 42 , , PUNCT cana-3976 392 43 vol vol NOUN cana-3976 392 44 . . PROPN cana-3976 392 45 35 35 NUM cana-3976 392 46 , , PUNCT cana-3976 392 47 no no DET cana-3976 392 48 5 5 NUM cana-3976 392 49 , , PUNCT cana-3976 392 50 p. p. NOUN cana-3976 392 51 1153โ€“1159 1153โ€“1159 NUM cana-3976 392 52 . . PUNCT cana-3976 393 1 [ [ X cana-3976 393 2 6 6 NUM cana-3976 393 3 ] ] X cana-3976 393 4 driscoll driscoll NOUN cana-3976 393 5 , , PUNCT cana-3976 393 6 i. i. NOUN cana-3976 393 7 ; ; PUNCT cana-3976 393 8 troncoso troncoso PROPN cana-3976 393 9 , , PUNCT cana-3976 393 10 j. j. PROPN cana-3976 393 11 asymptomatic asymptomatic PROPN cana-3976 393 12 alzheimer alzheimer PROPN cana-3976 393 13 โ€™s โ€™s PART cana-3976 393 14 disease disease NOUN cana-3976 393 15 : : PUNCT cana-3976 393 16 a a DET cana-3976 393 17 prodrome prodrome NOUN cana-3976 393 18 or or CCONJ cana-3976 393 19 a a DET cana-3976 393 20 state state NOUN cana-3976 393 21 of of ADP cana-3976 393 22 resilience resilience NOUN cana-3976 393 23 ? ? PUNCT cana-3976 394 1 curr curr PROPN cana-3976 394 2 . . PUNCT cana-3976 395 1 alzheimer alzheimer PROPN cana-3976 395 2 res res PROPN cana-3976 395 3 . . PROPN cana-3976 395 4 2011 2011 NUM cana-3976 395 5 , , PUNCT cana-3976 395 6 8 8 NUM cana-3976 395 7 , , PUNCT cana-3976 395 8 330โ€“335 330โ€“335 NUM cana-3976 395 9 . . PUNCT cana-3976 396 1 [ [ X cana-3976 396 2 7 7 NUM cana-3976 396 3 ] ] X cana-3976 396 4 thijskooi thijskooi NOUN cana-3976 396 5 , , PUNCT cana-3976 396 6 why why SCONJ cana-3976 396 7 skin skin NOUN cana-3976 396 8 lesions lesion NOUN cana-3976 396 9 are be AUX cana-3976 396 10 peanuts peanut NOUN cana-3976 396 11 and and CCONJ cana-3976 396 12 brain brain NOUN cana-3976 396 13 tumors tumor NOUN cana-3976 396 14 a a DET cana-3976 396 15 harder hard ADJ cana-3976 396 16 nut nut NOUN cana-3976 396 17 ( ( PUNCT cana-3976 396 18 2020 2020 NUM cana-3976 396 19 ) ) PUNCT cana-3976 396 20 , , PUNCT cana-3976 396 21 the the DET cana-3976 396 22 gradient gradient NOUN cana-3976 396 23 [ [ X cana-3976 396 24 8 8 NUM cana-3976 396 25 ] ] PUNCT cana-3976 396 26 a. a. NOUN cana-3976 396 27 gupta gupta PROPN cana-3976 396 28 , , PUNCT cana-3976 396 29 m. m. NOUN cana-3976 396 30 ayhan ayhan PROPN cana-3976 396 31 , , PUNCT cana-3976 396 32 and and CCONJ cana-3976 396 33 a. a. PROPN cana-3976 396 34 maida maida PROPN cana-3976 396 35 , , PUNCT cana-3976 396 36 natural natural ADJ cana-3976 396 37 image image NOUN cana-3976 396 38 bases basis NOUN cana-3976 396 39 to to PART cana-3976 396 40 represent represent VERB cana-3976 396 41 neuroimaging neuroimaging NOUN cana-3976 396 42 data datum NOUN cana-3976 396 43 ( ( PUNCT cana-3976 396 44 2013 2013 NUM cana-3976 396 45 ) ) PUNCT cana-3976 396 46 , , PUNCT cana-3976 396 47 international international ADJ cana-3976 396 48 conference conference NOUN cana-3976 396 49 on on ADP cana-3976 396 50 machine machine NOUN cana-3976 396 51 learning learning NOUN cana-3976 396 52 , , PUNCT cana-3976 396 53 p. p. NOUN cana-3976 396 54 987โ€“994 987โ€“994 NUM cana-3976 397 1 [ [ X cana-3976 397 2 9 9 NUM cana-3976 397 3 ] ] PUNCT cana-3976 397 4 a. a. NOUN cana-3976 397 5 payan payan NOUN cana-3976 397 6 and and CCONJ cana-3976 397 7 g. g. PROPN cana-3976 397 8 montana montana PROPN cana-3976 397 9 , , PUNCT cana-3976 397 10 predicting predict VERB cana-3976 397 11 alzheimer alzheimer PROPN cana-3976 397 12 โ€™s โ€™s PART cana-3976 397 13 disease disease NOUN cana-3976 397 14 : : PUNCT cana-3976 397 15 a a DET cana-3976 397 16 neuroimaging neuroimage VERB cana-3976 397 17 study study NOUN cana-3976 397 18 with with ADP cana-3976 397 19 3d 3d PROPN cana-3976 397 20 convolutional convolutional ADJ cana-3976 397 21 neural neural ADJ cana-3976 397 22 networks network NOUN cana-3976 397 23 ( ( PUNCT cana-3976 397 24 2015 2015 NUM cana-3976 397 25 ) ) PUNCT cana-3976 397 26 , , PUNCT cana-3976 397 27 arxivprepr arxivprepr NOUN cana-3976 397 28 . . PUNCT cana-3976 397 29 arxiv1502.02506 arxiv1502.02506 PROPN cana-3976 398 1 [ [ X cana-3976 398 2 10 10 NUM cana-3976 398 3 ] ] X cana-3976 398 4 zhao zhao X cana-3976 398 5 , , PUNCT cana-3976 398 6 jiaxi jiaxi PROPN cana-3976 398 7 & & CCONJ cana-3976 398 8 li li PROPN cana-3976 398 9 , , PUNCT cana-3976 398 10 kaixin kaixin PROPN cana-3976 398 11 & & CCONJ cana-3976 398 12 liao liao PROPN cana-3976 398 13 , , PUNCT cana-3976 398 14 xiaoyang xiaoyang PROPN cana-3976 398 15 . . PUNCT cana-3976 399 1 ( ( PUNCT cana-3976 399 2 2022 2022 NUM cana-3976 399 3 ) ) PUNCT cana-3976 399 4 . . PUNCT cana-3976 400 1 working work VERB cana-3976 400 2 status status NOUN cana-3976 400 3 and and CCONJ cana-3976 400 4 risk risk NOUN cana-3976 400 5 of of ADP cana-3976 400 6 alzheimer alzheimer PROPN cana-3976 400 7 's 's PART cana-3976 400 8 disease disease NOUN cana-3976 400 9 : : PUNCT cana-3976 400 10 a a DET cana-3976 400 11 mendelian mendelian ADJ cana-3976 400 12 randomization randomization NOUN cana-3976 400 13 study study NOUN cana-3976 400 14 . . PUNCT cana-3976 400 15 brain brain NOUN cana-3976 400 16 and and CCONJ cana-3976 400 17 behavior behavior NOUN cana-3976 400 18 . . PUNCT cana-3976 401 1 13 13 NUM cana-3976 401 2 . . X cana-3976 401 3 10.1002 10.1002 NUM cana-3976 401 4 / / SYM cana-3976 401 5 brb3.2834 brb3.2834 PROPN cana-3976 401 6 . . PUNCT cana-3976 402 1 [ [ X cana-3976 402 2 11 11 NUM cana-3976 402 3 ] ] X cana-3976 402 4 hosseinzadehkasani hosseinzadehkasani PROPN cana-3976 402 5 , , PUNCT cana-3976 402 6 payam payam PROPN cana-3976 402 7 & & CCONJ cana-3976 402 8 kim kim PROPN cana-3976 402 9 , , PUNCT cana-3976 402 10 jungโ€kyeom&kassani jungโ€kyeom&kassani PROPN cana-3976 402 11 , , PUNCT cana-3976 402 12 peyman peyman NOUN cana-3976 402 13 & & CCONJ cana-3976 402 14 kim kim PROPN cana-3976 402 15 , , PUNCT cana-3976 402 16 yeshin yeshin PROPN cana-3976 402 17 & & CCONJ cana-3976 402 18 kim kim PROPN cana-3976 402 19 , , PUNCT cana-3976 402 20 jeongโ€ah jeongโ€ah PROPN cana-3976 402 21 & & CCONJ cana-3976 402 22 park park PROPN cana-3976 402 23 , , PUNCT cana-3976 402 24 chihyun chihyun PROPN cana-3976 402 25 & & CCONJ cana-3976 402 26 yun yun PROPN cana-3976 402 27 , , PUNCT cana-3976 402 28 cheol cheol NOUN cana-3976 402 29 - - PUNCT cana-3976 402 30 heui heui PROPN cana-3976 402 31 & & CCONJ cana-3976 402 32 choi choi PROPN cana-3976 402 33 , , PUNCT cana-3976 402 34 sang sing VERB cana-3976 402 35 - - PUNCT cana-3976 402 36 hoon hoon PROPN cana-3976 402 37 & & CCONJ cana-3976 402 38 lee lee PROPN cana-3976 402 39 , , PUNCT cana-3976 402 40 sang sang VERB cana-3976 402 41 - - PUNCT cana-3976 402 42 ah ah INTJ cana-3976 402 43 & & CCONJ cana-3976 402 44 lee lee PROPN cana-3976 402 45 , , PUNCT cana-3976 402 46 seoโ€young seoโ€young PROPN cana-3976 402 47 & & CCONJ cana-3976 402 48 jang jang PROPN cana-3976 402 49 , , PUNCT cana-3976 402 50 jae jae PROPN cana-3976 402 51 won win VERB cana-3976 402 52 . . PUNCT cana-3976 403 1 ( ( PUNCT cana-3976 403 2 2022 2022 NUM cana-3976 403 3 ) ) PUNCT cana-3976 403 4 . . PUNCT cana-3976 404 1 a a DET cana-3976 404 2 machine machine NOUN cana-3976 404 3 learningโ€based learningโ€base VERB cana-3976 404 4 approach approach NOUN cana-3976 404 5 for for ADP cana-3976 404 6 classification classification NOUN cana-3976 404 7 of of ADP cana-3976 404 8 alzheimer alzheimer PROPN cana-3976 404 9 โ€™s โ€™s PART cana-3976 404 10 disease disease NOUN cana-3976 404 11 and and CCONJ cana-3976 404 12 its its PRON cana-3976 404 13 risk risk NOUN cana-3976 404 14 prediction prediction NOUN cana-3976 404 15 . . PUNCT cana-3976 405 1 alzheimer alzheimer PROPN cana-3976 405 2 's 's PART cana-3976 405 3 & & CCONJ cana-3976 405 4 dementia dementia PROPN cana-3976 405 5 . . PUNCT cana-3976 406 1 18 18 NUM cana-3976 406 2 . . X cana-3976 406 3 10.1002 10.1002 NUM cana-3976 406 4 / / SYM cana-3976 406 5 alz.064066 alz.064066 PROPN cana-3976 406 6 . . PUNCT cana-3976 407 1 [ [ X cana-3976 407 2 12 12 NUM cana-3976 407 3 ] ] PUNCT cana-3976 407 4 j. j. PROPN cana-3976 407 5 islam islam PROPN cana-3976 407 6 and and CCONJ cana-3976 407 7 y. y. PROPN cana-3976 407 8 zhang zhang PROPN cana-3976 407 9 , , PUNCT cana-3976 407 10 โ€œ " PUNCT cana-3976 407 11 an an DET cana-3976 407 12 ensemble ensemble NOUN cana-3976 407 13 of of ADP cana-3976 407 14 deep deep ADJ cana-3976 407 15 convolutional convolutional ADJ cana-3976 407 16 neural neural ADJ cana-3976 407 17 networks network NOUN cana-3976 407 18 for for ADP cana-3976 407 19 alzheimer alzheimer PROPN cana-3976 407 20 โ€™s โ€™s PART cana-3976 407 21 disease disease NOUN cana-3976 407 22 detection detection NOUN cana-3976 407 23 and and CCONJ cana-3976 407 24 classification classification NOUN cana-3976 407 25 , , PUNCT cana-3976 407 26 โ€ " PUNCT cana-3976 407 27 http://arxiv.org/abs/1712.01675 http://arxiv.org/abs/1712.01675 NOUN cana-3976 407 28 . . PUNCT cana-3976 408 1 [ [ X cana-3976 408 2 13 13 NUM cana-3976 408 3 ] ] X cana-3976 408 4 moradi moradi NOUN cana-3976 408 5 , , PUNCT cana-3976 408 6 elaheh&pepe elaheh&pepe PROPN cana-3976 408 7 , , PUNCT cana-3976 408 8 antonietta&gaser antonietta&gaser PROPN cana-3976 408 9 , , PUNCT cana-3976 408 10 christian christian PROPN cana-3976 408 11 & & CCONJ cana-3976 408 12 huttunen huttunen PROPN cana-3976 408 13 , , PUNCT cana-3976 408 14 heikki&tohka heikki&tohka PROPN cana-3976 408 15 , , PUNCT cana-3976 408 16 jussi jussi PROPN cana-3976 408 17 . . PUNCT cana-3976 409 1 ( ( PUNCT cana-3976 409 2 2014 2014 NUM cana-3976 409 3 ) ) PUNCT cana-3976 409 4 . . PUNCT cana-3976 410 1 machine machine NOUN cana-3976 410 2 learning learn VERB cana-3976 410 3 framework framework NOUN cana-3976 410 4 for for ADP cana-3976 410 5 early early ADJ cana-3976 410 6 mri mri NOUN cana-3976 410 7 - - PUNCT cana-3976 410 8 based base VERB cana-3976 410 9 alzheimer alzheimer NOUN cana-3976 410 10 's 's PART cana-3976 410 11 conversion conversion NOUN cana-3976 410 12 prediction prediction NOUN cana-3976 410 13 in in ADP cana-3976 410 14 mci mci PROPN cana-3976 410 15 subjects subject NOUN cana-3976 410 16 . . PUNCT cana-3976 411 1 neuroimage neuroimage NOUN cana-3976 411 2 . . PUNCT cana-3976 412 1 104 104 NUM cana-3976 412 2 . . PUNCT cana-3976 413 1 10.1016 10.1016 NUM cana-3976 413 2 / / SYM cana-3976 413 3 j.neuroimage.2014.10.002 j.neuroimage.2014.10.002 NOUN cana-3976 413 4 . . PUNCT cana-3976 414 1 [ [ X cana-3976 414 2 14 14 NUM cana-3976 414 3 ] ] X cana-3976 414 4 zhang zhang PROPN cana-3976 414 5 , , PUNCT cana-3976 414 6 yu yu PROPN cana-3976 414 7 - - PUNCT cana-3976 414 8 dong dong PROPN cana-3976 414 9 & & CCONJ cana-3976 414 10 dong dong PROPN cana-3976 414 11 , , PUNCT cana-3976 414 12 zhengchao zhengchao PROPN cana-3976 414 13 & & CCONJ cana-3976 414 14 phillips phillips PROPN cana-3976 414 15 , , PUNCT cana-3976 414 16 preetha preetha PROPN cana-3976 414 17 & & CCONJ cana-3976 414 18 wang wang PROPN cana-3976 414 19 , , PUNCT cana-3976 414 20 shuihua&ji shuihua&ji PROPN cana-3976 414 21 , , PUNCT cana-3976 414 22 genlin genlin PROPN cana-3976 414 23 & & CCONJ cana-3976 414 24 yang yang PROPN cana-3976 414 25 , , PUNCT cana-3976 414 26 jiquan jiquan PROPN cana-3976 414 27 & & CCONJ cana-3976 414 28 yuan yuan PROPN cana-3976 414 29 , , PUNCT cana-3976 414 30 ti ti PROPN cana-3976 414 31 - - NOUN cana-3976 414 32 fei fei NOUN cana-3976 414 33 . . PUNCT cana-3976 415 1 ( ( PUNCT cana-3976 415 2 2015 2015 NUM cana-3976 415 3 ) ) PUNCT cana-3976 415 4 . . PUNCT cana-3976 416 1 detection detection NOUN cana-3976 416 2 of of ADP cana-3976 416 3 subjects subject NOUN cana-3976 416 4 and and CCONJ cana-3976 416 5 brain brain NOUN cana-3976 416 6 regions region NOUN cana-3976 416 7 related relate VERB cana-3976 416 8 to to ADP cana-3976 416 9 alzheimer alzheimer PROPN cana-3976 416 10 's 's PART cana-3976 416 11 disease disease NOUN cana-3976 416 12 using use VERB cana-3976 416 13 3d 3d NUM cana-3976 416 14 mri mri NOUN cana-3976 416 15 scans scan NOUN cana-3976 416 16 based base VERB cana-3976 416 17 on on ADP cana-3976 416 18 eigenbrain eigenbrain NOUN cana-3976 416 19 and and CCONJ cana-3976 416 20 machine machine NOUN cana-3976 416 21 learning learning NOUN cana-3976 416 22 . . PUNCT cana-3976 417 1 frontiers frontier NOUN cana-3976 417 2 in in ADP cana-3976 417 3 computational computational ADJ cana-3976 417 4 neuroscience neuroscience NOUN cana-3976 417 5 . . PUNCT cana-3976 418 1 9 9 NUM cana-3976 418 2 . . X cana-3976 419 1 66 66 NUM cana-3976 419 2 . . PUNCT cana-3976 420 1 10.3389 10.3389 NUM cana-3976 420 2 / / SYM cana-3976 420 3 fncom.2015.00066 fncom.2015.00066 NOUN cana-3976 420 4 . . PUNCT cana-3976 421 1 [ [ X cana-3976 421 2 15 15 NUM cana-3976 421 3 ] ] X cana-3976 421 4 wang wang PROPN cana-3976 421 5 , , PUNCT cana-3976 421 6 qi qi PROPN cana-3976 421 7 & & CCONJ cana-3976 421 8 chen chen PROPN cana-3976 421 9 , , PUNCT cana-3976 421 10 siwei siwei PROPN cana-3976 421 11 & & CCONJ cana-3976 421 12 wang wang PROPN cana-3976 421 13 , , PUNCT cana-3976 421 14 he he PRON cana-3976 421 15 & & CCONJ cana-3976 421 16 chen chen PROPN cana-3976 421 17 , , PUNCT cana-3976 421 18 luzeng luzeng PROPN cana-3976 421 19 & & CCONJ cana-3976 421 20 sun sun PROPN cana-3976 421 21 , , PUNCT cana-3976 421 22 yongan yongan PROPN cana-3976 421 23 & & CCONJ cana-3976 421 24 yan yan PROPN cana-3976 421 25 , , PUNCT cana-3976 421 26 guiying guiying NOUN cana-3976 421 27 . . PUNCT cana-3976 421 28 ( ( PUNCT cana-3976 421 29 2021 2021 NUM cana-3976 421 30 ) ) PUNCT cana-3976 421 31 . . PUNCT cana-3976 422 1 predicting predict VERB cana-3976 422 2 brain brain NOUN cana-3976 422 3 regions region NOUN cana-3976 422 4 related relate VERB cana-3976 422 5 to to ADP cana-3976 422 6 alzheimer alzheimer PROPN cana-3976 422 7 's 's PART cana-3976 422 8 disease disease NOUN cana-3976 422 9 based base VERB cana-3976 422 10 on on ADP cana-3976 422 11 global global ADJ cana-3976 422 12 feature feature NOUN cana-3976 422 13 . . PUNCT cana-3976 423 1 frontiers frontier NOUN cana-3976 423 2 in in ADP cana-3976 423 3 computational computational ADJ cana-3976 423 4 neuroscience neuroscience NOUN cana-3976 423 5 . . PUNCT cana-3976 424 1 15 15 NUM cana-3976 424 2 . . X cana-3976 424 3 10.3389 10.3389 NUM cana-3976 424 4 / / SYM cana-3976 424 5 fncom.2021.659838 fncom.2021.659838 NOUN cana-3976 424 6 . . PUNCT cana-3976 425 1 [ [ X cana-3976 425 2 16 16 NUM cana-3976 425 3 ] ] X cana-3976 425 4 wen wen PROPN cana-3976 425 5 , , PUNCT cana-3976 425 6 junhao&thibeau junhao&thibeau PROPN cana-3976 425 7 - - PUNCT cana-3976 425 8 sutre sutre PROPN cana-3976 425 9 , , PUNCT cana-3976 425 10 elina elina PROPN cana-3976 425 11 & & CCONJ cana-3976 425 12 diaz diaz PROPN cana-3976 425 13 - - PUNCT cana-3976 425 14 melo melo PROPN cana-3976 425 15 , , PUNCT cana-3976 425 16 mauricio mauricio PROPN cana-3976 425 17 & & CCONJ cana-3976 425 18 samper samper PROPN cana-3976 425 19 - - PUNCT cana-3976 425 20 gonzalez gonzalez PROPN cana-3976 425 21 , , PUNCT cana-3976 425 22 jorge jorge NOUN cana-3976 425 23 & & CCONJ cana-3976 425 24 routier routier NOUN cana-3976 425 25 , , PUNCT cana-3976 425 26 alexandre&bottani alexandre&bottani PROPN cana-3976 425 27 , , PUNCT cana-3976 425 28 simona&dormont simona&dormont ADJ cana-3976 425 29 , , PUNCT cana-3976 425 30 didier didier NOUN cana-3976 425 31 & & CCONJ cana-3976 425 32 durrleman durrleman PROPN cana-3976 425 33 , , PUNCT cana-3976 425 34 stanley stanley PROPN cana-3976 425 35 & & CCONJ cana-3976 425 36 burgos burgos PROPN cana-3976 425 37 , , PUNCT cana-3976 425 38 ninon&colliot ninon&colliot NOUN cana-3976 425 39 , , PUNCT cana-3976 425 40 olivier olivier NOUN cana-3976 425 41 . . PUNCT cana-3976 426 1 ( ( PUNCT cana-3976 426 2 2020 2020 NUM cana-3976 426 3 ) ) PUNCT cana-3976 426 4 . . PUNCT cana-3976 427 1 convolutional convolutional ADJ cana-3976 427 2 neural neural ADJ cana-3976 427 3 networks network NOUN cana-3976 427 4 for for ADP cana-3976 427 5 classification classification NOUN cana-3976 427 6 of of ADP cana-3976 427 7 alzheimer alzheimer PROPN cana-3976 427 8 's 's PART cana-3976 427 9 disease disease NOUN cana-3976 427 10 : : PUNCT cana-3976 427 11 overview overview NOUN cana-3976 427 12 and and CCONJ cana-3976 427 13 reproducible reproducible ADJ cana-3976 427 14 evaluation evaluation NOUN cana-3976 427 15 . . PUNCT cana-3976 428 1 medical medical ADJ cana-3976 428 2 image image NOUN cana-3976 428 3 analysis analysis NOUN cana-3976 428 4 . . PUNCT cana-3976 429 1 63 63 NUM cana-3976 429 2 . . PUNCT cana-3976 429 3 101694 101694 NUM cana-3976 429 4 . . PUNCT cana-3976 430 1 10.1016 10.1016 NUM cana-3976 430 2 / / SYM cana-3976 430 3 j.media.2020.101694 j.media.2020.101694 NOUN cana-3976 430 4 . . PUNCT cana-3976 431 1 [ [ X cana-3976 431 2 17 17 NUM cana-3976 431 3 ] ] X cana-3976 431 4 zheng zheng PROPN cana-3976 431 5 , , PUNCT cana-3976 431 6 yineng&guo yineng&guo PROPN cana-3976 431 7 , , PUNCT cana-3976 431 8 haoming haoming NOUN cana-3976 431 9 & & CCONJ cana-3976 431 10 zhang zhang PROPN cana-3976 431 11 , , PUNCT cana-3976 431 12 lijuan lijuan PROPN cana-3976 431 13 & & CCONJ cana-3976 431 14 wu wu PROPN cana-3976 431 15 , , PUNCT cana-3976 431 16 jiahui jiahui PROPN cana-3976 431 17 & & CCONJ cana-3976 431 18 li li PROPN cana-3976 431 19 , , PUNCT cana-3976 431 20 qi qi PROPN cana-3976 431 21 & & CCONJ cana-3976 431 22 lv lv PROPN cana-3976 431 23 , , PUNCT cana-3976 431 24 fajin fajin NOUN cana-3976 431 25 . . PUNCT cana-3976 431 26 ( ( PUNCT cana-3976 431 27 2019 2019 NUM cana-3976 431 28 ) ) PUNCT cana-3976 431 29 . . PUNCT cana-3976 432 1 machine machine NOUN cana-3976 432 2 learning learning NOUN cana-3976 432 3 - - PUNCT cana-3976 432 4 based base VERB cana-3976 432 5 framework framework NOUN cana-3976 432 6 for for ADP cana-3976 432 7 differential differential ADJ cana-3976 432 8 diagnosis diagnosis NOUN cana-3976 432 9 between between ADP cana-3976 432 10 vascular vascular ADJ cana-3976 432 11 dementia dementia NOUN cana-3976 432 12 communications communication NOUN cana-3976 432 13 on on ADP cana-3976 432 14 applied apply VERB cana-3976 432 15 nonlinear nonlinear ADJ cana-3976 432 16 analysis analysis NOUN cana-3976 432 17 issn issn NOUN cana-3976 432 18 : : PUNCT cana-3976 432 19 1074 1074 NUM cana-3976 432 20 - - PUNCT cana-3976 432 21 133x 133x NUM cana-3976 432 22 vol vol NOUN cana-3976 432 23 32 32 NUM cana-3976 432 24 no no NOUN cana-3976 432 25 . . PUNCT cana-3976 433 1 9s 9s NUM cana-3976 433 2 ( ( PUNCT cana-3976 433 3 2025 2025 NUM cana-3976 433 4 ) ) PUNCT cana-3976 433 5 717 717 NUM cana-3976 433 6 https://internationalpubls.com https://internationalpubls.com X cana-3976 433 7 and and CCONJ cana-3976 433 8 alzheimer alzheimer PROPN cana-3976 433 9 's 's PART cana-3976 433 10 disease disease NOUN cana-3976 433 11 using use VERB cana-3976 433 12 structural structural ADJ cana-3976 433 13 mri mri NOUN cana-3976 433 14 features feature NOUN cana-3976 433 15 . . PUNCT cana-3976 434 1 frontiers frontier NOUN cana-3976 434 2 in in ADP cana-3976 434 3 neurology neurology NOUN cana-3976 434 4 . . PUNCT cana-3976 435 1 10 10 NUM cana-3976 435 2 . . NUM cana-3976 435 3 1097 1097 NUM cana-3976 435 4 . . PUNCT cana-3976 435 5 10.3389 10.3389 NUM cana-3976 435 6 / / SYM cana-3976 435 7 fneur.2019.01097 fneur.2019.01097 NOUN cana-3976 435 8 . . PUNCT cana-3976 436 1 [ [ X cana-3976 436 2 18 18 NUM cana-3976 436 3 ] ] X cana-3976 436 4 maqsood maqsood PROPN cana-3976 436 5 , , PUNCT cana-3976 436 6 muazzam&nazir muazzam&nazir PROPN cana-3976 436 7 , , PUNCT cana-3976 436 8 faria faria PROPN cana-3976 436 9 & & CCONJ cana-3976 436 10 khan khan PROPN cana-3976 436 11 , , PUNCT cana-3976 436 12 umair&aadil umair&aadil PROPN cana-3976 436 13 , , PUNCT cana-3976 436 14 farhan farhan PROPN cana-3976 436 15 & & CCONJ cana-3976 436 16 jamal jamal PROPN cana-3976 436 17 , , PUNCT cana-3976 436 18 habibullah&mehmood habibullah&mehmood PROPN cana-3976 436 19 , , PUNCT cana-3976 436 20 irfan irfan PROPN cana-3976 436 21 & & CCONJ cana-3976 436 22 song song PROPN cana-3976 436 23 , , PUNCT cana-3976 436 24 oh oh INTJ cana-3976 436 25 - - PUNCT cana-3976 436 26 young young PROPN cana-3976 436 27 & & CCONJ cana-3976 436 28 yasir yasir PROPN cana-3976 436 29 , , PUNCT cana-3976 436 30 somiya somiya NOUN cana-3976 436 31 . . PUNCT cana-3976 437 1 ( ( PUNCT cana-3976 437 2 2019 2019 NUM cana-3976 437 3 ) ) PUNCT cana-3976 437 4 . . PUNCT cana-3976 438 1 transfer transfer NOUN cana-3976 438 2 learning learning NOUN cana-3976 438 3 assisted assist VERB cana-3976 438 4 classification classification NOUN cana-3976 438 5 and and CCONJ cana-3976 438 6 detection detection NOUN cana-3976 438 7 of of ADP cana-3976 438 8 alzheimer alzheimer PROPN cana-3976 438 9 โ€™s โ€™s PART cana-3976 438 10 disease disease NOUN cana-3976 438 11 stages stage NOUN cana-3976 438 12 using use VERB cana-3976 438 13 3d 3d NUM cana-3976 438 14 mri mri NOUN cana-3976 438 15 scans scan NOUN cana-3976 438 16 . . PUNCT cana-3976 439 1 sensors sensor NOUN cana-3976 439 2 . . PUNCT cana-3976 440 1 19 19 NUM cana-3976 440 2 . . NOUN cana-3976 440 3 2645 2645 NUM cana-3976 440 4 . . PUNCT cana-3976 441 1 10.3390 10.3390 NUM cana-3976 441 2 / / SYM cana-3976 441 3 s19112645 s19112645 NOUN cana-3976 441 4 . . PUNCT cana-3976 442 1 [ [ X cana-3976 442 2 19 19 NUM cana-3976 442 3 ] ] SYM cana-3976 442 4 ferreira ferreira PROPN cana-3976 442 5 , , PUNCT cana-3976 442 6 luiz&rondina luiz&rondina PROPN cana-3976 442 7 , , PUNCT cana-3976 442 8 jane jane PROPN cana-3976 442 9 & & CCONJ cana-3976 442 10 kubo kubo PROPN cana-3976 442 11 , , PUNCT cana-3976 442 12 rodrigo rodrigo PROPN cana-3976 442 13 & & CCONJ cana-3976 442 14 ono ono PROPN cana-3976 442 15 , , PUNCT cana-3976 442 16 carla carla PROPN cana-3976 442 17 & & CCONJ cana-3976 442 18 leite leite PROPN cana-3976 442 19 , , PUNCT cana-3976 442 20 claudia claudia PROPN cana-3976 442 21 & & CCONJ cana-3976 442 22 smid smid PROPN cana-3976 442 23 , , PUNCT cana-3976 442 24 jerusa&bottino jerusa&bottino PROPN cana-3976 442 25 , , PUNCT cana-3976 442 26 cรกssio&nitrini cรกssio&nitrini PROPN cana-3976 442 27 , , PUNCT cana-3976 442 28 ricardo ricardo PROPN cana-3976 442 29 & & CCONJ cana-3976 442 30 busatto busatto PROPN cana-3976 442 31 , , PUNCT cana-3976 442 32 geraldo geraldo PROPN cana-3976 442 33 & & CCONJ cana-3976 442 34 duran duran PROPN cana-3976 442 35 , , PUNCT cana-3976 442 36 fabio fabio PROPN cana-3976 442 37 & & CCONJ cana-3976 442 38 buchpiguel buchpiguel PROPN cana-3976 442 39 , , PUNCT cana-3976 442 40 carlos carlos PROPN cana-3976 442 41 . . PUNCT cana-3976 443 1 ( ( PUNCT cana-3976 443 2 2017 2017 NUM cana-3976 443 3 ) ) PUNCT cana-3976 443 4 . . PUNCT cana-3976 444 1 support support NOUN cana-3976 444 2 vector vector NOUN cana-3976 444 3 machine machine NOUN cana-3976 444 4 - - PUNCT cana-3976 444 5 based base VERB cana-3976 444 6 classification classification NOUN cana-3976 444 7 of of ADP cana-3976 444 8 neuroimages neuroimage NOUN cana-3976 444 9 in in ADP cana-3976 444 10 alzheimer alzheimer PROPN cana-3976 444 11 โ€™s โ€™s PART cana-3976 444 12 disease disease NOUN cana-3976 444 13 : : PUNCT cana-3976 444 14 direct direct ADJ cana-3976 444 15 comparison comparison NOUN cana-3976 444 16 of of ADP cana-3976 444 17 fdg fdg PROPN cana-3976 444 18 - - PUNCT cana-3976 444 19 pet pet ADJ cana-3976 444 20 , , PUNCT cana-3976 444 21 rcbf rcbf NOUN cana-3976 444 22 - - PUNCT cana-3976 444 23 spect spect NOUN cana-3976 444 24 and and CCONJ cana-3976 444 25 mri mri NOUN cana-3976 444 26 data datum NOUN cana-3976 444 27 acquired acquire VERB cana-3976 444 28 from from ADP cana-3976 444 29 the the DET cana-3976 444 30 same same ADJ cana-3976 444 31 individuals individual NOUN cana-3976 444 32 . . PUNCT cana-3976 445 1 revistabrasileira revistabrasileira PROPN cana-3976 445 2 de de PROPN cana-3976 445 3 psiquiatria psiquiatria PROPN cana-3976 445 4 . . PUNCT cana-3976 446 1 40 40 NUM cana-3976 446 2 . . PUNCT cana-3976 447 1 10.1590/1516 10.1590/1516 NUM cana-3976 447 2 - - SYM cana-3976 447 3 4446 4446 NUM cana-3976 447 4 - - SYM cana-3976 447 5 2016 2016 NUM cana-3976 447 6 - - PUNCT cana-3976 447 7 2083 2083 NUM cana-3976 447 8 . . PUNCT cana-3976 448 1 [ [ X cana-3976 448 2 20 20 NUM cana-3976 448 3 ] ] X cana-3976 448 4 hodabadr hodabadr NOUN cana-3976 448 5 , , PUNCT cana-3976 448 6 t.a.r t.a.r PROPN cana-3976 448 7 . . PROPN cana-3976 448 8 , , PUNCT cana-3976 448 9 carmack carmack PROPN cana-3976 448 10 , , PUNCT cana-3976 448 11 c.l c.l PROPN cana-3976 448 12 . . PROPN cana-3976 448 13 , , PUNCT cana-3976 448 14 kashy kashy ADJ cana-3976 448 15 , , PUNCT cana-3976 448 16 d.a d.a PROPN cana-3976 448 17 . . PROPN cana-3976 448 18 , , PUNCT cana-3976 448 19 cristofanilli cristofanilli PROPN cana-3976 448 20 , , PUNCT cana-3976 448 21 m. m. NOUN cana-3976 448 22 : : PUNCT cana-3976 448 23 ๅŸบๅ› ็š„ๆ”นๅ˜nih ๅŸบๅ› ็š„ๆ”นๅ˜nih PROPN cana-3976 448 24 public public ADJ cana-3976 448 25 access access NOUN cana-3976 448 26 . . PUNCT cana-3976 449 1 bone bone NOUN cana-3976 449 2 23(1 23(1 NUM cana-3976 449 3 ) ) PUNCT cana-3976 449 4 , , PUNCT cana-3976 449 5 1โ€“7 1โ€“7 NUM cana-3976 449 6 ( ( PUNCT cana-3976 449 7 2011 2011 NUM cana-3976 449 8 ) ) PUNCT cana-3976 449 9 . . PUNCT cana-3976 450 1 https://doi.org/10.1161/circulationaha.110.956839 https://doi.org/10.1161/circulationaha.110.956839 ADJ cana-3976 450 2 . . PUNCT cana-3976 451 1 [ [ X cana-3976 451 2 21 21 NUM cana-3976 451 3 ] ] X cana-3976 451 4 morris morris PROPN cana-3976 451 5 , , PUNCT cana-3976 451 6 j.c j.c PROPN cana-3976 451 7 . . PROPN cana-3976 451 8 the the DET cana-3976 451 9 clinical clinical ADJ cana-3976 451 10 dementia dementia NOUN cana-3976 451 11 rating rating NOUN cana-3976 451 12 ( ( PUNCT cana-3976 451 13 cdr cdr NOUN cana-3976 451 14 ): ): PUNCT cana-3976 451 15 current current ADJ cana-3976 451 16 version version NOUN cana-3976 451 17 and and CCONJ cana-3976 451 18 scoring scoring NOUN cana-3976 451 19 rules rule NOUN cana-3976 451 20 . . PUNCT cana-3976 452 1 neurology neurology NOUN cana-3976 452 2 1993 1993 NUM cana-3976 452 3 , , PUNCT cana-3976 452 4 43 43 NUM cana-3976 452 5 , , PUNCT cana-3976 452 6 2412โ€“2414 2412โ€“2414 NUM cana-3976 452 7 . . PUNCT cana-3976 453 1 [ [ X cana-3976 453 2 22 22 NUM cana-3976 453 3 ] ] X cana-3976 453 4 open open ADJ cana-3976 453 5 access access NOUN cana-3976 453 6 series series NOUN cana-3976 453 7 of of ADP cana-3976 453 8 imaging imaging NOUN cana-3976 453 9 studies study NOUN cana-3976 453 10 ( ( PUNCT cana-3976 453 11 oasis oasis NOUN cana-3976 453 12 ) ) PUNCT cana-3976 453 13 . . PUNCT cana-3976 454 1 available available ADJ cana-3976 454 2 online online ADV cana-3976 454 3 : : PUNCT cana-3976 455 1 http://www.oasisbrains.org/. http://www.oasisbrains.org/. ADP cana-3976 455 2 [ [ X cana-3976 455 3 23 23 NUM cana-3976 455 4 ] ] SYM cana-3976 455 5 buckner buckner PROPN cana-3976 455 6 , , PUNCT cana-3976 455 7 r.l r.l PROPN cana-3976 455 8 . . PROPN cana-3976 455 9 ; ; PUNCT cana-3976 455 10 head head PROPN cana-3976 455 11 , , PUNCT cana-3976 455 12 d. d. PROPN cana-3976 455 13 ; ; PUNCT cana-3976 455 14 parker parker PROPN cana-3976 455 15 , , PUNCT cana-3976 455 16 j. j. PROPN cana-3976 455 17 ; ; PUNCT cana-3976 456 1 fotenos fotenos PROPN cana-3976 456 2 , , PUNCT cana-3976 456 3 a.f a.f PROPN cana-3976 456 4 . . PROPN cana-3976 456 5 ; ; PUNCT cana-3976 456 6 marcus marcus PROPN cana-3976 456 7 , , PUNCT cana-3976 456 8 d. d. PROPN cana-3976 456 9 ; ; PUNCT cana-3976 456 10 morris morris PROPN cana-3976 456 11 , , PUNCT cana-3976 456 12 j.c j.c PROPN cana-3976 456 13 . . PROPN cana-3976 456 14 ; ; PUNCT cana-3976 456 15 snyder snyder PROPN cana-3976 456 16 , , PUNCT cana-3976 456 17 a.z a.z PROPN cana-3976 456 18 . . PROPN cana-3976 456 19 a a DET cana-3976 456 20 unified unified ADJ cana-3976 456 21 approach approach NOUN cana-3976 456 22 for for ADP cana-3976 456 23 morphometric morphometric ADJ cana-3976 456 24 and and CCONJ cana-3976 456 25 functional functional ADJ cana-3976 456 26 data datum NOUN cana-3976 456 27 analysis analysis NOUN cana-3976 456 28 in in ADP cana-3976 456 29 young young ADJ cana-3976 456 30 , , PUNCT cana-3976 456 31 old old ADJ cana-3976 456 32 , , PUNCT cana-3976 456 33 and and CCONJ cana-3976 456 34 demented demented ADJ cana-3976 456 35 adults adult NOUN cana-3976 456 36 using use VERB cana-3976 456 37 automated automate VERB cana-3976 456 38 atlas atlas PROPN cana-3976 456 39 - - PUNCT cana-3976 456 40 based base VERB cana-3976 456 41 head head NOUN cana-3976 456 42 size size NOUN cana-3976 456 43 normalization normalization NOUN cana-3976 456 44 : : PUNCT cana-3976 456 45 reliability reliability NOUN cana-3976 456 46 and and CCONJ cana-3976 456 47 validation validation NOUN cana-3976 456 48 against against ADP cana-3976 456 49 manual manual ADJ cana-3976 456 50 measurement measurement NOUN cana-3976 456 51 of of ADP cana-3976 456 52 total total ADJ cana-3976 456 53 intracranial intracranial ADJ cana-3976 456 54 volume volume NOUN cana-3976 456 55 . . PUNCT cana-3976 457 1 neuroimage neuroimage NOUN cana-3976 457 2 2004 2004 NUM cana-3976 457 3 , , PUNCT cana-3976 457 4 23 23 NUM cana-3976 457 5 , , PUNCT cana-3976 457 6 724โ€“738 724โ€“738 NUM cana-3976 457 7 . . PUNCT cana-3976 458 1 [ [ X cana-3976 458 2 24 24 NUM cana-3976 458 3 ] ] X cana-3976 458 4 dreiseitl dreiseitl PROPN cana-3976 458 5 , , PUNCT cana-3976 458 6 s. s. PROPN cana-3976 458 7 , , PUNCT cana-3976 458 8 ohno ohno PROPN cana-3976 458 9 - - PUNCT cana-3976 458 10 machado machado PROPN cana-3976 458 11 , , PUNCT cana-3976 458 12 l. l. PROPN cana-3976 458 13 : : PUNCT cana-3976 458 14 logistic logistic ADJ cana-3976 458 15 regression regression NOUN cana-3976 458 16 and and CCONJ cana-3976 458 17 artificial artificial ADJ cana-3976 458 18 neural neural ADJ cana-3976 458 19 network network NOUN cana-3976 458 20 classification classification NOUN cana-3976 458 21 models model NOUN cana-3976 458 22 : : PUNCT cana-3976 458 23 a a DET cana-3976 458 24 methodology methodology NOUN cana-3976 458 25 review review NOUN cana-3976 458 26 . . PUNCT cana-3976 459 1 j. j. PROPN cana-3976 459 2 biomed biome VERB cana-3976 459 3 . . PUNCT cana-3976 460 1 inf inf PROPN cana-3976 460 2 . . PUNCT cana-3976 461 1 35(5โ€“6 35(5โ€“6 NUM cana-3976 461 2 ) ) PUNCT cana-3976 461 3 , , PUNCT cana-3976 461 4 352โ€“359 352โ€“359 NUM cana-3976 461 5 ( ( PUNCT cana-3976 461 6 2002 2002 NUM cana-3976 461 7 ) ) PUNCT cana-3976 461 8 . . PUNCT cana-3976 462 1 https://doi.org/10.1016/s1532-0464(03)00034-0 https://doi.org/10.1016/s1532-0464(03)00034-0 PROPN cana-3976 462 2 . . PUNCT cana-3976 463 1 [ [ X cana-3976 463 2 25 25 NUM cana-3976 463 3 ] ] PUNCT cana-3976 463 4 maroco maroco NOUN cana-3976 463 5 , , PUNCT cana-3976 463 6 j. j. PROPN cana-3976 463 7 , , PUNCT cana-3976 463 8 silva silva PROPN cana-3976 463 9 , , PUNCT cana-3976 463 10 d. d. PROPN cana-3976 463 11 , , PUNCT cana-3976 463 12 rodrigues rodrigues PROPN cana-3976 463 13 , , PUNCT cana-3976 463 14 a. a. PROPN cana-3976 463 15 , , PUNCT cana-3976 463 16 guerreiro guerreiro PROPN cana-3976 463 17 , , PUNCT cana-3976 463 18 m. m. NOUN cana-3976 463 19 , , PUNCT cana-3976 463 20 santana santana PROPN cana-3976 463 21 , , PUNCT cana-3976 463 22 i. i. PROPN cana-3976 463 23 , , PUNCT cana-3976 463 24 de de X cana-3976 463 25 mendonรงa mendonรงa X cana-3976 463 26 , , PUNCT cana-3976 463 27 a. a. NOUN cana-3976 463 28 : : PUNCT cana-3976 463 29 data datum NOUN cana-3976 463 30 mining mining NOUN cana-3976 463 31 methods method NOUN cana-3976 463 32 in in ADP cana-3976 463 33 the the DET cana-3976 463 34 prediction prediction NOUN cana-3976 463 35 of of ADP cana-3976 463 36 dementia dementia NOUN cana-3976 463 37 : : PUNCT cana-3976 463 38 a a DET cana-3976 463 39 real real ADJ cana-3976 463 40 - - PUNCT cana-3976 463 41 data datum NOUN cana-3976 463 42 comparison comparison NOUN cana-3976 463 43 of of ADP cana-3976 463 44 the the DET cana-3976 463 45 accuracy accuracy NOUN cana-3976 463 46 , , PUNCT cana-3976 463 47 sensitivity sensitivity NOUN cana-3976 463 48 and and CCONJ cana-3976 463 49 specificity specificity NOUN cana-3976 463 50 of of ADP cana-3976 463 51 linear linear ADJ cana-3976 463 52 discriminant discriminant ADJ cana-3976 463 53 analysis analysis NOUN cana-3976 463 54 , , PUNCT cana-3976 463 55 logistic logistic ADJ cana-3976 463 56 regression regression NOUN cana-3976 463 57 , , PUNCT cana-3976 463 58 neural neural ADJ cana-3976 463 59 networks network NOUN cana-3976 463 60 , , PUNCT cana-3976 463 61 support support VERB cana-3976 463 62 vector vector NOUN cana-3976 463 63 machines machine NOUN cana-3976 463 64 , , PUNCT cana-3976 463 65 classification classification NOUN cana-3976 463 66 trees tree NOUN cana-3976 463 67 and and CCONJ cana-3976 463 68 random random ADJ cana-3976 463 69 forests forest NOUN cana-3976 463 70 . . PUNCT cana-3976 464 1 bmc bmc NOUN cana-3976 464 2 res re NOUN cana-3976 464 3 . . PUNCT cana-3976 465 1 notes notes PROPN cana-3976 465 2 4(1 4(1 NOUN cana-3976 465 3 ) ) PUNCT cana-3976 465 4 , , PUNCT cana-3976 465 5 1โ€“14 1โ€“14 PROPN cana-3976 465 6 ( ( PUNCT cana-3976 465 7 2011 2011 NUM cana-3976 465 8 ) ) PUNCT cana-3976 465 9 . . PUNCT cana-3976 466 1 [ [ X cana-3976 466 2 26 26 NUM cana-3976 466 3 ] ] X cana-3976 466 4 savio savio NOUN cana-3976 466 5 , , PUNCT cana-3976 466 6 a. a. NOUN cana-3976 466 7 : : PUNCT cana-3976 466 8 supervised supervise VERB cana-3976 466 9 classification classification NOUN cana-3976 466 10 using use VERB cana-3976 466 11 deformation deformation NOUN cana-3976 466 12 - - PUNCT cana-3976 466 13 based base VERB cana-3976 466 14 features feature NOUN cana-3976 466 15 for for ADP cana-3976 466 16 alzheimer alzheimer PROPN cana-3976 466 17 โ€™s โ€™s PART cana-3976 466 18 disease disease NOUN cana-3976 466 19 detection detection NOUN cana-3976 466 20 on on ADP cana-3976 466 21 the the DET cana-3976 466 22 oasis oasis NOUN cana-3976 466 23 cross cross ADJ cana-3976 466 24 - - ADJ cana-3976 466 25 sectional sectional ADJ cana-3976 466 26 database database NOUN cana-3976 466 27 . . PUNCT cana-3976 467 1 front front ADJ cana-3976 467 2 . . PUNCT cana-3976 468 1 artif artif INTJ cana-3976 468 2 . . PUNCT cana-3976 469 1 intell intell PROPN cana-3976 469 2 . . PUNCT cana-3976 470 1 appl appl PROPN cana-3976 470 2 . . PROPN cana-3976 471 1 243 243 NUM cana-3976 471 2 , , PUNCT cana-3976 471 3 2191โ€“2200 2191โ€“2200 NUM cana-3976 471 4 ( ( PUNCT cana-3976 471 5 2012 2012 NUM cana-3976 471 6 ) ) PUNCT cana-3976 471 7 . . PUNCT cana-3976 472 1 [ [ X cana-3976 472 2 27 27 NUM cana-3976 472 3 ] ] X cana-3976 472 4 cao cao PROPN cana-3976 472 5 , , PUNCT cana-3976 472 6 j. j. PROPN cana-3976 472 7 ; ; PUNCT cana-3976 472 8 su su PROPN cana-3976 472 9 , , PUNCT cana-3976 472 10 z. z. PROPN cana-3976 472 11 ; ; PUNCT cana-3976 472 12 yu yu PROPN cana-3976 472 13 , , PUNCT cana-3976 472 14 l. l. PROPN cana-3976 472 15 ; ; PUNCT cana-3976 472 16 chang chang PROPN cana-3976 472 17 , , PUNCT cana-3976 472 18 d. d. PROPN cana-3976 472 19 ; ; PUNCT cana-3976 472 20 li li PROPN cana-3976 472 21 , , PUNCT cana-3976 472 22 x. x. PROPN cana-3976 472 23 ; ; PUNCT cana-3976 472 24 ma ma PROPN cana-3976 472 25 , , PUNCT cana-3976 472 26 z. z. PROPN cana-3976 472 27 softmax softmax PROPN cana-3976 472 28 cross cross PROPN cana-3976 472 29 entropy entropy PROPN cana-3976 472 30 loss loss PROPN cana-3976 472 31 with with ADP cana-3976 472 32 unbiased unbiased ADJ cana-3976 472 33 decision decision NOUN cana-3976 472 34 boundary boundary ADJ cana-3976 472 35 for for ADP cana-3976 472 36 image image NOUN cana-3976 472 37 classification classification NOUN cana-3976 472 38 . . PUNCT cana-3976 473 1 in in ADP cana-3976 473 2 proceedings proceeding NOUN cana-3976 473 3 of of ADP cana-3976 473 4 the the DET cana-3976 473 5 2018 2018 NUM cana-3976 473 6 chinese chinese ADJ cana-3976 473 7 automation automation NOUN cana-3976 473 8 congress congress PROPN cana-3976 473 9 ( ( PUNCT cana-3976 473 10 cac cac PROPN cana-3976 473 11 ) ) PUNCT cana-3976 473 12 , , PUNCT cana-3976 473 13 xiโ€™an xiโ€™an PROPN cana-3976 473 14 , , PUNCT cana-3976 473 15 china china PROPN cana-3976 473 16 , , PUNCT cana-3976 473 17 30 30 NUM cana-3976 473 18 novemberโ€“2 novemberโ€“2 CCONJ cana-3976 473 19 december december PROPN cana-3976 473 20 2018 2018 NUM cana-3976 473 21 ; ; PUNCT cana-3976 473 22 p. p. NOUN cana-3976 473 23 2028 2028 NUM cana-3976 473 24 . . PUNCT cana-3976 474 1 [ [ X cana-3976 474 2 28 28 NUM cana-3976 474 3 ] ] X cana-3976 474 4 zhang zhang PROPN cana-3976 474 5 , , PUNCT cana-3976 474 6 y. y. PROPN cana-3976 474 7 ; ; PUNCT cana-3976 474 8 yao yao PROPN cana-3976 474 9 , , PUNCT cana-3976 474 10 j. j. PROPN cana-3976 474 11 gini gini PROPN cana-3976 474 12 objective objective ADJ cana-3976 474 13 functions function NOUN cana-3976 474 14 for for ADP cana-3976 474 15 three three NUM cana-3976 474 16 - - PUNCT cana-3976 474 17 way way NOUN cana-3976 474 18 classifications classification NOUN cana-3976 474 19 . . PUNCT cana-3976 475 1 int int NOUN cana-3976 475 2 . . PUNCT cana-3976 476 1 j. j. PROPN cana-3976 476 2 approx approx PROPN cana-3976 476 3 . . PUNCT cana-3976 477 1 reason reason NOUN cana-3976 477 2 . . PUNCT cana-3976 478 1 2017 2017 NUM cana-3976 478 2 , , PUNCT cana-3976 478 3 81 81 NUM cana-3976 478 4 , , PUNCT cana-3976 478 5 103โ€“114 103โ€“114 NUM cana-3976 478 6 . . PUNCT