id sid tid token lemma pos cana-572 1 1 communications communication NOUN cana-572 1 2 on on ADP cana-572 1 3 applied apply VERB cana-572 1 4 nonlinear nonlinear ADJ cana-572 1 5 analysis analysis NOUN cana-572 1 6 issn issn NOUN cana-572 1 7 : : PUNCT cana-572 1 8 1074 1074 NUM cana-572 1 9 - - PUNCT cana-572 1 10 133x 133x NUM cana-572 1 11 vol vol NOUN cana-572 1 12 31 31 NUM cana-572 1 13 no no NOUN cana-572 1 14 . . NOUN cana-572 1 15 2 2 NUM cana-572 1 16 ( ( PUNCT cana-572 1 17 2024 2024 NUM cana-572 1 18 ) ) PUNCT cana-572 1 19 331 331 NUM cana-572 1 20 https://internationalpubls.com https://internationalpubls.com X cana-572 1 21 integration integration NOUN cana-572 1 22 of of ADP cana-572 1 23 complex complex ADJ cana-572 1 24 mathematical mathematical ADJ cana-572 1 25 approaches approach NOUN cana-572 1 26 and and CCONJ cana-572 1 27 statistical statistical ADJ cana-572 1 28 methodologies methodology NOUN cana-572 1 29 in in ADP cana-572 1 30 machine machine NOUN cana-572 1 31 learning learn VERB cana-572 1 32 for for ADP cana-572 1 33 design design NOUN cana-572 1 34 of of ADP cana-572 1 35 robust robust ADJ cana-572 1 36 prediction prediction NOUN cana-572 1 37 models model NOUN cana-572 1 38 sarita sarita PROPN cana-572 1 39 silaich1 silaich1 PROPN cana-572 1 40 , , PUNCT cana-572 1 41 dr dr PROPN cana-572 1 42 rajesh rajesh PROPN cana-572 1 43 yadav2 yadav2 PROPN cana-572 1 44 1 1 NUM cana-572 1 45 phd phd NOUN cana-572 1 46 scholar scholar NOUN cana-572 1 47 , , PUNCT cana-572 1 48 department department NOUN cana-572 1 49 of of ADP cana-572 1 50 computer computer NOUN cana-572 1 51 science science NOUN cana-572 1 52 and and CCONJ cana-572 1 53 engineering engineering NOUN cana-572 1 54 , , PUNCT cana-572 1 55 mody mody PROPN cana-572 1 56 university university PROPN cana-572 1 57 of of ADP cana-572 1 58 science science NOUN cana-572 1 59 and and CCONJ cana-572 1 60 technology technology NOUN cana-572 1 61 , , PUNCT cana-572 1 62 rajasthan rajasthan PROPN cana-572 1 63 , , PUNCT cana-572 1 64 india india PROPN cana-572 1 65 2 2 NUM cana-572 1 66 assistant assistant NOUN cana-572 1 67 professor professor NOUN cana-572 1 68 , , PUNCT cana-572 1 69 department department NOUN cana-572 1 70 of of ADP cana-572 1 71 computer computer NOUN cana-572 1 72 science science NOUN cana-572 1 73 and and CCONJ cana-572 1 74 engineering engineering NOUN cana-572 1 75 , , PUNCT cana-572 1 76 mody mody PROPN cana-572 1 77 university university PROPN cana-572 1 78 of of ADP cana-572 1 79 science science NOUN cana-572 1 80 and and CCONJ cana-572 1 81 technology technology NOUN cana-572 1 82 , , PUNCT cana-572 1 83 rajasthan rajasthan PROPN cana-572 1 84 , , PUNCT cana-572 1 85 india india PROPN cana-572 1 86 email email NOUN cana-572 1 87 : : PUNCT cana-572 1 88 sarita.bits@gmail.com sarita.bits@gmail.com X cana-572 1 89 1 1 NUM cana-572 1 90 , , PUNCT cana-572 1 91 yadav.rajesh27@gmail.com yadav.rajesh27@gmail.com X cana-572 1 92 2 2 NUM cana-572 1 93 article article NOUN cana-572 1 94 history history NOUN cana-572 1 95 : : PUNCT cana-572 1 96 received receive VERB cana-572 1 97 : : PUNCT cana-572 1 98 12 12 NUM cana-572 1 99 - - PUNCT cana-572 1 100 02 02 NUM cana-572 1 101 - - PUNCT cana-572 1 102 2024 2024 NUM cana-572 1 103 revised revise VERB cana-572 1 104 : : PUNCT cana-572 1 105 26 26 NUM cana-572 1 106 - - PUNCT cana-572 1 107 04 04 NUM cana-572 1 108 - - PUNCT cana-572 1 109 2024 2024 NUM cana-572 1 110 accepted accept VERB cana-572 1 111 : : PUNCT cana-572 1 112 06 06 NUM cana-572 1 113 - - SYM cana-572 1 114 05 05 NUM cana-572 1 115 - - PUNCT cana-572 1 116 2024 2024 NUM cana-572 1 117 abstract abstract NOUN cana-572 1 118 : : PUNCT cana-572 1 119 the the DET cana-572 1 120 disease disease NOUN cana-572 1 121 known know VERB cana-572 1 122 as as ADP cana-572 1 123 breast breast NOUN cana-572 1 124 cancer cancer NOUN cana-572 1 125 continues continue VERB cana-572 1 126 to to PART cana-572 1 127 be be AUX cana-572 1 128 one one NUM cana-572 1 129 of of ADP cana-572 1 130 the the DET cana-572 1 131 most most ADV cana-572 1 132 common common ADJ cana-572 1 133 and and CCONJ cana-572 1 134 potentially potentially ADV cana-572 1 135 fatal fatal ADJ cana-572 1 136 diseases disease NOUN cana-572 1 137 that that PRON cana-572 1 138 affect affect VERB cana-572 1 139 women woman NOUN cana-572 1 140 all all ADV cana-572 1 141 over over ADP cana-572 1 142 the the DET cana-572 1 143 world world NOUN cana-572 1 144 . . PUNCT cana-572 2 1 in in ADP cana-572 2 2 order order NOUN cana-572 2 3 to to PART cana-572 2 4 provide provide VERB cana-572 2 5 effective effective ADJ cana-572 2 6 therapy therapy NOUN cana-572 2 7 and and CCONJ cana-572 2 8 more more ADV cana-572 2 9 favorable favorable ADJ cana-572 2 10 outcomes outcome NOUN cana-572 2 11 for for ADP cana-572 2 12 patients patient NOUN cana-572 2 13 , , PUNCT cana-572 2 14 early early ADJ cana-572 2 15 detection detection NOUN cana-572 2 16 and and CCONJ cana-572 2 17 correct correct ADJ cana-572 2 18 diagnosis diagnosis NOUN cana-572 2 19 are be AUX cana-572 2 20 absolutely absolutely ADV cana-572 2 21 necessary necessary ADJ cana-572 2 22 . . PUNCT cana-572 3 1 this this DET cana-572 3 2 research research NOUN cana-572 3 3 explores explore VERB cana-572 3 4 the the DET cana-572 3 5 integration integration NOUN cana-572 3 6 of of ADP cana-572 3 7 operational operational ADJ cana-572 3 8 research research NOUN cana-572 3 9 ( ( PUNCT cana-572 3 10 or or CCONJ cana-572 3 11 ) ) PUNCT cana-572 3 12 methodologies methodology NOUN cana-572 3 13 and and CCONJ cana-572 3 14 advanced advanced ADJ cana-572 3 15 statistical statistical ADJ cana-572 3 16 methods method NOUN cana-572 3 17 within within ADP cana-572 3 18 machine machine NOUN cana-572 3 19 learning learn VERB cana-572 3 20 frameworks framework NOUN cana-572 3 21 to to PART cana-572 3 22 enhance enhance VERB cana-572 3 23 the the DET cana-572 3 24 prediction prediction NOUN cana-572 3 25 accuracy accuracy NOUN cana-572 3 26 of of ADP cana-572 3 27 breast breast NOUN cana-572 3 28 cancer cancer NOUN cana-572 3 29 outcomes outcome NOUN cana-572 3 30 . . PUNCT cana-572 4 1 by by ADP cana-572 4 2 harnessing harness VERB cana-572 4 3 the the DET cana-572 4 4 power power NOUN cana-572 4 5 of of ADP cana-572 4 6 nonlinear nonlinear ADJ cana-572 4 7 optimization optimization NOUN cana-572 4 8 and and CCONJ cana-572 4 9 statistical statistical ADJ cana-572 4 10 techniques technique NOUN cana-572 4 11 , , PUNCT cana-572 4 12 including include VERB cana-572 4 13 regression regression NOUN cana-572 4 14 analysis analysis NOUN cana-572 4 15 and and CCONJ cana-572 4 16 probability probability NOUN cana-572 4 17 distribution distribution NOUN cana-572 4 18 models model NOUN cana-572 4 19 , , PUNCT cana-572 4 20 we we PRON cana-572 4 21 aim aim VERB cana-572 4 22 to to PART cana-572 4 23 refine refine VERB cana-572 4 24 the the DET cana-572 4 25 predictive predictive ADJ cana-572 4 26 capabilities capability NOUN cana-572 4 27 of of ADP cana-572 4 28 existing exist VERB cana-572 4 29 algorithms algorithm NOUN cana-572 4 30 . . PUNCT cana-572 5 1 the the DET cana-572 5 2 research research NOUN cana-572 5 3 employs employ VERB cana-572 5 4 a a DET cana-572 5 5 comprehensive comprehensive ADJ cana-572 5 6 dataset dataset NOUN cana-572 5 7 derived derive VERB cana-572 5 8 from from ADP cana-572 5 9 clinical clinical ADJ cana-572 5 10 trials trial NOUN cana-572 5 11 and and CCONJ cana-572 5 12 patient patient ADJ cana-572 5 13 records record NOUN cana-572 5 14 , , PUNCT cana-572 5 15 analyzed analyze VERB cana-572 5 16 through through ADP cana-572 5 17 a a DET cana-572 5 18 series series NOUN cana-572 5 19 of of ADP cana-572 5 20 machine machine NOUN cana-572 5 21 learning learning NOUN cana-572 5 22 models model NOUN cana-572 5 23 that that PRON cana-572 5 24 incorporate incorporate VERB cana-572 5 25 elements element NOUN cana-572 5 26 of of ADP cana-572 5 27 combinatorial combinatorial ADJ cana-572 5 28 optimization optimization NOUN cana-572 5 29 , , PUNCT cana-572 5 30 decision decision NOUN cana-572 5 31 analysis analysis NOUN cana-572 5 32 , , PUNCT cana-572 5 33 and and CCONJ cana-572 5 34 stochastic stochastic ADJ cana-572 5 35 modeling modeling NOUN cana-572 5 36 . . PUNCT cana-572 6 1 key key ADJ cana-572 6 2 performance performance NOUN cana-572 6 3 metrics metric NOUN cana-572 6 4 , , PUNCT cana-572 6 5 such such ADJ cana-572 6 6 as as ADP cana-572 6 7 accuracy accuracy NOUN cana-572 6 8 , , PUNCT cana-572 6 9 sensitivity sensitivity NOUN cana-572 6 10 , , PUNCT cana-572 6 11 and and CCONJ cana-572 6 12 specificity specificity NOUN cana-572 6 13 , , PUNCT cana-572 6 14 are be AUX cana-572 6 15 evaluated evaluate VERB cana-572 6 16 against against ADP cana-572 6 17 standard standard ADJ cana-572 6 18 benchmarks benchmark NOUN cana-572 6 19 to to PART cana-572 6 20 determine determine VERB cana-572 6 21 the the DET cana-572 6 22 efficacy efficacy NOUN cana-572 6 23 of of ADP cana-572 6 24 the the DET cana-572 6 25 integrated integrate VERB cana-572 6 26 approaches approach NOUN cana-572 6 27 . . PUNCT cana-572 7 1 preliminary preliminary ADJ cana-572 7 2 results result NOUN cana-572 7 3 indicate indicate VERB cana-572 7 4 that that SCONJ cana-572 7 5 incorporating incorporate VERB cana-572 7 6 or or CCONJ cana-572 7 7 and and CCONJ cana-572 7 8 statistical statistical ADJ cana-572 7 9 methods method NOUN cana-572 7 10 significantly significantly ADV cana-572 7 11 improves improve VERB cana-572 7 12 model model NOUN cana-572 7 13 robustness robustness NOUN cana-572 7 14 and and CCONJ cana-572 7 15 predictive predictive ADJ cana-572 7 16 accuracy accuracy NOUN cana-572 7 17 . . PUNCT cana-572 8 1 the the DET cana-572 8 2 study study NOUN cana-572 8 3 not not PART cana-572 8 4 only only ADV cana-572 8 5 demonstrates demonstrate VERB cana-572 8 6 the the DET cana-572 8 7 potential potential NOUN cana-572 8 8 of of ADP cana-572 8 9 applied apply VERB cana-572 8 10 mathematics mathematic NOUN cana-572 8 11 in in ADP cana-572 8 12 medical medical ADJ cana-572 8 13 diagnostics diagnostic NOUN cana-572 8 14 but but CCONJ cana-572 8 15 also also ADV cana-572 8 16 provides provide VERB cana-572 8 17 a a DET cana-572 8 18 framework framework NOUN cana-572 8 19 for for ADP cana-572 8 20 future future ADJ cana-572 8 21 research research NOUN cana-572 8 22 in in ADP cana-572 8 23 enhancing enhance VERB cana-572 8 24 machine machine NOUN cana-572 8 25 learning learning NOUN cana-572 8 26 models model NOUN cana-572 8 27 for for ADP cana-572 8 28 health health NOUN cana-572 8 29 outcomes outcome NOUN cana-572 8 30 prediction prediction NOUN cana-572 8 31 through through ADP cana-572 8 32 mathematical mathematical ADJ cana-572 8 33 innovations innovation NOUN cana-572 8 34 . . PUNCT cana-572 9 1 this this DET cana-572 9 2 investigation investigation NOUN cana-572 9 3 contributes contribute VERB cana-572 9 4 to to ADP cana-572 9 5 the the DET cana-572 9 6 field field NOUN cana-572 9 7 of of ADP cana-572 9 8 mathematical mathematical ADJ cana-572 9 9 oncology oncology NOUN cana-572 9 10 by by ADP cana-572 9 11 demonstrating demonstrate VERB cana-572 9 12 how how SCONJ cana-572 9 13 applied apply VERB cana-572 9 14 nonlinear nonlinear ADJ cana-572 9 15 analysis analysis NOUN cana-572 9 16 can can AUX cana-572 9 17 bridge bridge VERB cana-572 9 18 the the DET cana-572 9 19 gap gap NOUN cana-572 9 20 between between ADP cana-572 9 21 theoretical theoretical ADJ cana-572 9 22 mathematical mathematical ADJ cana-572 9 23 approaches approach NOUN cana-572 9 24 and and CCONJ cana-572 9 25 practical practical ADJ cana-572 9 26 clinical clinical ADJ cana-572 9 27 applications application NOUN cana-572 9 28 , , PUNCT cana-572 9 29 offering offer VERB cana-572 9 30 new new ADJ cana-572 9 31 pathways pathway NOUN cana-572 9 32 for for ADP cana-572 9 33 early early ADJ cana-572 9 34 and and CCONJ cana-572 9 35 more more ADV cana-572 9 36 accurate accurate ADJ cana-572 9 37 detection detection NOUN cana-572 9 38 of of ADP cana-572 9 39 breast breast NOUN cana-572 9 40 cancer cancer NOUN cana-572 9 41 . . PUNCT cana-572 10 1 keywords keyword NOUN cana-572 10 2 : : PUNCT cana-572 10 3 operational operational ADJ cana-572 10 4 research research NOUN cana-572 10 5 , , PUNCT cana-572 10 6 advanced advanced ADJ cana-572 10 7 statistical statistical ADJ cana-572 10 8 methods method NOUN cana-572 10 9 , , PUNCT cana-572 10 10 machine machine NOUN cana-572 10 11 learning learning NOUN cana-572 10 12 , , PUNCT cana-572 10 13 breast breast NOUN cana-572 10 14 cancer cancer NOUN cana-572 10 15 prediction prediction NOUN cana-572 10 16 , , PUNCT cana-572 10 17 nonlinear nonlinear ADJ cana-572 10 18 optimization optimization NOUN cana-572 10 19 , , PUNCT cana-572 10 20 regression regression VERB cana-572 10 21 analysis analysis NOUN cana-572 10 22 , , PUNCT cana-572 10 23 probability probability NOUN cana-572 10 24 models model NOUN cana-572 10 25 , , PUNCT cana-572 10 26 combinatorial combinatorial ADJ cana-572 10 27 optimization optimization NOUN cana-572 10 28 , , PUNCT cana-572 10 29 mathematical mathematical ADJ cana-572 10 30 oncology oncology NOUN cana-572 10 31 , , PUNCT cana-572 10 32 clinical clinical ADJ cana-572 10 33 applications application NOUN cana-572 10 34 . . PUNCT cana-572 11 1 1 1 X cana-572 11 2 . . X cana-572 11 3 introduction introduction NOUN cana-572 11 4 breast breast NOUN cana-572 11 5 cancer cancer NOUN cana-572 11 6 is be AUX cana-572 11 7 a a DET cana-572 11 8 major major ADJ cana-572 11 9 public public ADJ cana-572 11 10 health health NOUN cana-572 11 11 issue issue NOUN cana-572 11 12 globally globally ADV cana-572 11 13 , , PUNCT cana-572 11 14 with with ADP cana-572 11 15 early early ADJ cana-572 11 16 detection detection NOUN cana-572 11 17 significantly significantly ADV cana-572 11 18 increasing increase VERB cana-572 11 19 the the DET cana-572 11 20 chances chance NOUN cana-572 11 21 of of ADP cana-572 11 22 successful successful ADJ cana-572 11 23 treatment treatment NOUN cana-572 11 24 and and CCONJ cana-572 11 25 survival survival NOUN cana-572 11 26 . . PUNCT cana-572 12 1 traditional traditional ADJ cana-572 12 2 diagnostic diagnostic ADJ cana-572 12 3 methods method NOUN cana-572 12 4 include include VERB cana-572 12 5 mammography mammography NOUN cana-572 12 6 , , PUNCT cana-572 12 7 ultrasound ultrasound NOUN cana-572 12 8 , , PUNCT cana-572 12 9 and and CCONJ cana-572 12 10 biopsies biopsy NOUN cana-572 12 11 , , PUNCT cana-572 12 12 which which PRON cana-572 12 13 are be AUX cana-572 12 14 often often ADV cana-572 12 15 complemented complement VERB cana-572 12 16 by by ADP cana-572 12 17 predictive predictive ADJ cana-572 12 18 modeling modeling NOUN cana-572 12 19 to to PART cana-572 12 20 identify identify VERB cana-572 12 21 high high ADJ cana-572 12 22 - - PUNCT cana-572 12 23 risk risk NOUN cana-572 12 24 cases case NOUN cana-572 12 25 early early ADV cana-572 12 26 . . PUNCT cana-572 13 1 machine machine NOUN cana-572 13 2 learning learning NOUN cana-572 13 3 ( ( PUNCT cana-572 13 4 ml ml NOUN cana-572 13 5 ) ) PUNCT cana-572 13 6 models model NOUN cana-572 13 7 have have AUX cana-572 13 8 increasingly increasingly ADV cana-572 13 9 been be AUX cana-572 13 10 applied apply VERB cana-572 13 11 to to PART cana-572 13 12 improve improve VERB cana-572 13 13 the the DET cana-572 13 14 accuracy accuracy NOUN cana-572 13 15 and and CCONJ cana-572 13 16 efficiency efficiency NOUN cana-572 13 17 of of ADP cana-572 13 18 these these DET cana-572 13 19 predictions prediction NOUN cana-572 13 20 . . PUNCT cana-572 14 1 operational operational ADJ cana-572 14 2 research research NOUN cana-572 14 3 communications communication NOUN cana-572 14 4 on on ADP cana-572 14 5 applied apply VERB cana-572 14 6 nonlinear nonlinear ADJ cana-572 14 7 analysis analysis NOUN cana-572 14 8 issn issn NOUN cana-572 14 9 : : PUNCT cana-572 14 10 1074 1074 NUM cana-572 14 11 - - PUNCT cana-572 14 12 133x 133x NUM cana-572 14 13 vol vol NOUN cana-572 14 14 31 31 NUM cana-572 14 15 no no NOUN cana-572 14 16 . . NOUN cana-572 14 17 2 2 NUM cana-572 14 18 ( ( PUNCT cana-572 14 19 2024 2024 NUM cana-572 14 20 ) ) PUNCT cana-572 14 21 332 332 NUM cana-572 14 22 https://internationalpubls.com https://internationalpubls.com X cana-572 14 23 ( ( PUNCT cana-572 14 24 or or CCONJ cana-572 14 25 ) ) PUNCT cana-572 14 26 and and CCONJ cana-572 14 27 advanced advanced ADJ cana-572 14 28 statistical statistical ADJ cana-572 14 29 methods method NOUN cana-572 14 30 provide provide VERB cana-572 14 31 robust robust ADJ cana-572 14 32 frameworks framework NOUN cana-572 14 33 to to PART cana-572 14 34 enhance enhance VERB cana-572 14 35 these these DET cana-572 14 36 machine machine NOUN cana-572 14 37 learning learning NOUN cana-572 14 38 models model NOUN cana-572 14 39 . . PUNCT cana-572 15 1 or or CCONJ cana-572 15 2 , , PUNCT cana-572 15 3 primarily primarily ADV cana-572 15 4 concerned concern VERB cana-572 15 5 with with ADP cana-572 15 6 optimizing optimize VERB cana-572 15 7 complex complex ADJ cana-572 15 8 operations operation NOUN cana-572 15 9 and and CCONJ cana-572 15 10 decisionmaking decisionmake VERB cana-572 15 11 processes process NOUN cana-572 15 12 , , PUNCT cana-572 15 13 applies apply VERB cana-572 15 14 various various ADJ cana-572 15 15 mathematical mathematical ADJ cana-572 15 16 techniques technique NOUN cana-572 15 17 to to PART cana-572 15 18 maximize maximize VERB cana-572 15 19 efficiency efficiency NOUN cana-572 15 20 and and CCONJ cana-572 15 21 outcomes outcome NOUN cana-572 15 22 . . PUNCT cana-572 16 1 in in ADP cana-572 16 2 the the DET cana-572 16 3 context context NOUN cana-572 16 4 of of ADP cana-572 16 5 breast breast NOUN cana-572 16 6 cancer cancer NOUN cana-572 16 7 prediction prediction NOUN cana-572 16 8 , , PUNCT cana-572 16 9 or or CCONJ cana-572 16 10 can can AUX cana-572 16 11 optimize optimize VERB cana-572 16 12 how how SCONJ cana-572 16 13 predictive predictive ADJ cana-572 16 14 models model NOUN cana-572 16 15 handle handle VERB cana-572 16 16 data datum NOUN cana-572 16 17 , , PUNCT cana-572 16 18 make make VERB cana-572 16 19 classifications classification NOUN cana-572 16 20 , , PUNCT cana-572 16 21 and and CCONJ cana-572 16 22 even even ADV cana-572 16 23 determine determine VERB cana-572 16 24 the the DET cana-572 16 25 best good ADJ cana-572 16 26 sequences sequence NOUN cana-572 16 27 of of ADP cana-572 16 28 diagnostic diagnostic ADJ cana-572 16 29 tests test NOUN cana-572 16 30 . . PUNCT cana-572 17 1 statistical statistical ADJ cana-572 17 2 methods method NOUN cana-572 17 3 , , PUNCT cana-572 17 4 especially especially ADV cana-572 17 5 those those PRON cana-572 17 6 involving involve VERB cana-572 17 7 advanced advanced ADJ cana-572 17 8 calculations calculation NOUN cana-572 17 9 like like ADP cana-572 17 10 logistic logistic ADJ cana-572 17 11 regression regression NOUN cana-572 17 12 , , PUNCT cana-572 17 13 bayesian bayesian NOUN cana-572 17 14 inference inference NOUN cana-572 17 15 , , PUNCT cana-572 17 16 and and CCONJ cana-572 17 17 survival survival NOUN cana-572 17 18 analysis analysis NOUN cana-572 17 19 , , PUNCT cana-572 17 20 are be AUX cana-572 17 21 pivotal pivotal ADJ cana-572 17 22 in in ADP cana-572 17 23 interpreting interpret VERB cana-572 17 24 medical medical ADJ cana-572 17 25 data datum NOUN cana-572 17 26 . . PUNCT cana-572 18 1 these these DET cana-572 18 2 methods method NOUN cana-572 18 3 help help VERB cana-572 18 4 in in ADP cana-572 18 5 understanding understand VERB cana-572 18 6 the the DET cana-572 18 7 relationships relationship NOUN cana-572 18 8 between between ADP cana-572 18 9 various various ADJ cana-572 18 10 risk risk NOUN cana-572 18 11 factors factor NOUN cana-572 18 12 and and CCONJ cana-572 18 13 the the DET cana-572 18 14 likelihood likelihood NOUN cana-572 18 15 of of ADP cana-572 18 16 developing develop VERB cana-572 18 17 breast breast NOUN cana-572 18 18 cancer cancer NOUN cana-572 18 19 . . PUNCT cana-572 19 1 the the DET cana-572 19 2 integration integration NOUN cana-572 19 3 of of ADP cana-572 19 4 these these DET cana-572 19 5 statistical statistical ADJ cana-572 19 6 methods method NOUN cana-572 19 7 into into ADP cana-572 19 8 machine machine NOUN cana-572 19 9 learning learning NOUN cana-572 19 10 models model NOUN cana-572 19 11 ensures ensure VERB cana-572 19 12 that that SCONJ cana-572 19 13 the the DET cana-572 19 14 predictions prediction NOUN cana-572 19 15 are be AUX cana-572 19 16 not not PART cana-572 19 17 only only ADV cana-572 19 18 based base VERB cana-572 19 19 on on ADP cana-572 19 20 patterns pattern NOUN cana-572 19 21 in in ADP cana-572 19 22 the the DET cana-572 19 23 data datum NOUN cana-572 19 24 but but CCONJ cana-572 19 25 are be AUX cana-572 19 26 also also ADV cana-572 19 27 statistically statistically ADV cana-572 19 28 sound sound ADJ cana-572 19 29 , , PUNCT cana-572 19 30 reflecting reflect VERB cana-572 19 31 true true ADJ cana-572 19 32 correlations correlation NOUN cana-572 19 33 and and CCONJ cana-572 19 34 causations causation NOUN cana-572 19 35 . . PUNCT cana-572 20 1 the the DET cana-572 20 2 synergy synergy NOUN cana-572 20 3 between between ADP cana-572 20 4 machine machine NOUN cana-572 20 5 learning learning NOUN cana-572 20 6 , , PUNCT cana-572 20 7 operational operational ADJ cana-572 20 8 research research NOUN cana-572 20 9 , , PUNCT cana-572 20 10 and and CCONJ cana-572 20 11 advanced advanced ADJ cana-572 20 12 statistics statistic NOUN cana-572 20 13 is be AUX cana-572 20 14 potentiated potentiate VERB cana-572 20 15 through through ADP cana-572 20 16 several several ADJ cana-572 20 17 key key ADJ cana-572 20 18 areas area NOUN cana-572 20 19 : : PUNCT cana-572 20 20 1 1 X cana-572 20 21 . . X cana-572 20 22 data datum NOUN cana-572 20 23 optimization optimization NOUN cana-572 20 24 : : PUNCT cana-572 20 25 or or CCONJ cana-572 20 26 techniques technique NOUN cana-572 20 27 can can AUX cana-572 20 28 optimize optimize VERB cana-572 20 29 data datum NOUN cana-572 20 30 preprocessing preprocessing NOUN cana-572 20 31 , , PUNCT cana-572 20 32 selection selection NOUN cana-572 20 33 , , PUNCT cana-572 20 34 and and CCONJ cana-572 20 35 reduction reduction NOUN cana-572 20 36 to to PART cana-572 20 37 enhance enhance VERB cana-572 20 38 the the DET cana-572 20 39 quality quality NOUN cana-572 20 40 and and CCONJ cana-572 20 41 speed speed NOUN cana-572 20 42 of of ADP cana-572 20 43 machine machine NOUN cana-572 20 44 learning learn VERB cana-572 20 45 algorithms algorithm NOUN cana-572 20 46 . . PUNCT cana-572 21 1 2 2 X cana-572 21 2 . . PUNCT cana-572 21 3 model model NOUN cana-572 21 4 selection selection NOUN cana-572 21 5 and and CCONJ cana-572 21 6 tuning tuning NOUN cana-572 21 7 : : PUNCT cana-572 21 8 advanced advanced ADJ cana-572 21 9 statistical statistical ADJ cana-572 21 10 methods method NOUN cana-572 21 11 aid aid NOUN cana-572 21 12 in in ADP cana-572 21 13 selecting select VERB cana-572 21 14 the the DET cana-572 21 15 right right ADJ cana-572 21 16 model model NOUN cana-572 21 17 and and CCONJ cana-572 21 18 tuning tune VERB cana-572 21 19 parameters parameter NOUN cana-572 21 20 to to PART cana-572 21 21 improve improve VERB cana-572 21 22 prediction prediction NOUN cana-572 21 23 accuracy accuracy NOUN cana-572 21 24 and and CCONJ cana-572 21 25 reduce reduce VERB cana-572 21 26 overfitting overfitting NOUN cana-572 21 27 . . PUNCT cana-572 22 1 3 3 X cana-572 22 2 . . X cana-572 22 3 algorithm algorithm NOUN cana-572 22 4 enhancement enhancement NOUN cana-572 22 5 : : PUNCT cana-572 22 6 by by ADP cana-572 22 7 incorporating incorporate VERB cana-572 22 8 or or CCONJ cana-572 22 9 algorithms algorithm NOUN cana-572 22 10 such such ADJ cana-572 22 11 as as ADP cana-572 22 12 linear linear PROPN cana-572 22 13 programming programming NOUN cana-572 22 14 , , PUNCT cana-572 22 15 decision decision NOUN cana-572 22 16 trees tree NOUN cana-572 22 17 , , PUNCT cana-572 22 18 and and CCONJ cana-572 22 19 network network NOUN cana-572 22 20 flows flow NOUN cana-572 22 21 , , PUNCT cana-572 22 22 machine machine NOUN cana-572 22 23 learning learning NOUN cana-572 22 24 models model NOUN cana-572 22 25 can can AUX cana-572 22 26 be be AUX cana-572 22 27 refined refine VERB cana-572 22 28 to to PART cana-572 22 29 handle handle VERB cana-572 22 30 specific specific ADJ cana-572 22 31 complexities complexity NOUN cana-572 22 32 of of ADP cana-572 22 33 breast breast NOUN cana-572 22 34 cancer cancer NOUN cana-572 22 35 data datum NOUN cana-572 22 36 more more ADV cana-572 22 37 effectively effectively ADV cana-572 22 38 . . PUNCT cana-572 23 1 in in ADP cana-572 23 2 developing develop VERB cana-572 23 3 robust robust ADJ cana-572 23 4 predictive predictive ADJ cana-572 23 5 models model NOUN cana-572 23 6 , , PUNCT cana-572 23 7 it it PRON cana-572 23 8 is be AUX cana-572 23 9 essential essential ADJ cana-572 23 10 to to PART cana-572 23 11 apply apply VERB cana-572 23 12 a a DET cana-572 23 13 structured structured ADJ cana-572 23 14 approach approach NOUN cana-572 23 15 to to PART cana-572 23 16 integrate integrate VERB cana-572 23 17 these these DET cana-572 23 18 disciplines discipline NOUN cana-572 23 19 . . PUNCT cana-572 24 1 the the DET cana-572 24 2 following follow VERB cana-572 24 3 equations equation NOUN cana-572 24 4 provide provide VERB cana-572 24 5 a a DET cana-572 24 6 mathematical mathematical ADJ cana-572 24 7 basis basis NOUN cana-572 24 8 for for ADP cana-572 24 9 this this DET cana-572 24 10 integration integration NOUN cana-572 24 11 , , PUNCT cana-572 24 12 illustrating illustrate VERB cana-572 24 13 how how SCONJ cana-572 24 14 various various ADJ cana-572 24 15 operational operational ADJ cana-572 24 16 research research NOUN cana-572 24 17 and and CCONJ cana-572 24 18 statistical statistical ADJ cana-572 24 19 techniques technique NOUN cana-572 24 20 can can AUX cana-572 24 21 be be AUX cana-572 24 22 applied apply VERB cana-572 24 23 to to PART cana-572 24 24 refine refine VERB cana-572 24 25 machine machine NOUN cana-572 24 26 learning learning NOUN cana-572 24 27 algorithms algorithm NOUN cana-572 24 28 specifically specifically ADV cana-572 24 29 tailored tailor VERB cana-572 24 30 for for ADP cana-572 24 31 breast breast NOUN cana-572 24 32 cancer cancer NOUN cana-572 24 33 prediction prediction NOUN cana-572 24 34 . . PUNCT cana-572 25 1 the the DET cana-572 25 2 general general ADJ cana-572 25 3 logistic logistic ADJ cana-572 25 4 regression regression NOUN cana-572 25 5 model model NOUN cana-572 25 6 for for ADP cana-572 25 7 binary binary ADJ cana-572 25 8 outcomes outcome NOUN cana-572 25 9 , , PUNCT cana-572 25 10 where where SCONJ cana-572 25 11 y y PROPN cana-572 25 12 is be AUX cana-572 25 13 the the DET cana-572 25 14 binary binary ADJ cana-572 25 15 response response NOUN cana-572 25 16 ( ( PUNCT cana-572 25 17 breast breast NOUN cana-572 25 18 cancer cancer NOUN cana-572 25 19 occurrence occurrence NOUN cana-572 25 20 or or CCONJ cana-572 25 21 not not PART cana-572 25 22 ) ) PUNCT cana-572 25 23 and and CCONJ cana-572 25 24 x x PRON cana-572 25 25 represents represent VERB cana-572 25 26 the the DET cana-572 25 27 input input NOUN cana-572 25 28 features feature NOUN cana-572 25 29 ( ( PUNCT cana-572 25 30 e.g. e.g. ADV cana-572 25 31 , , PUNCT cana-572 25 32 age age NOUN cana-572 25 33 , , PUNCT cana-572 25 34 genetics genetic NOUN cana-572 25 35 , , PUNCT cana-572 25 36 lifestyle lifestyle NOUN cana-572 25 37 factors factor NOUN cana-572 25 38 ): ): PUNCT cana-572 25 39 π‘Œ π‘Œ PROPN cana-572 25 40 = = SYM cana-572 25 41 1 1 NUM cana-572 25 42 1+π‘’βˆ’|π‘₯0+𝛽1π‘₯1+𝛽2π‘₯2+β‹―+𝛽𝑛π‘₯𝑛| 1+π‘’βˆ’|π‘₯0+𝛽1π‘₯1+𝛽2π‘₯2+β‹―+𝛽𝑛π‘₯𝑛| NUM cana-572 25 43 ( ( PUNCT cana-572 25 44 1 1 NUM cana-572 25 45 ) ) PUNCT cana-572 25 46 the the DET cana-572 25 47 likelihood likelihood NOUN cana-572 25 48 function function NOUN cana-572 25 49 for for ADP cana-572 25 50 the the DET cana-572 25 51 logistic logistic ADJ cana-572 25 52 regression regression NOUN cana-572 25 53 , , PUNCT cana-572 25 54 used use VERB cana-572 25 55 to to PART cana-572 25 56 estimate estimate VERB cana-572 25 57 the the DET cana-572 25 58 parameters parameter NOUN cana-572 25 59 𝛽 𝛽 NOUN cana-572 25 60 : : PUNCT cana-572 25 61 𝐿(𝛽 𝐿(𝛽 NUM cana-572 25 62 ) ) PUNCT cana-572 25 63 = = SYM cana-572 25 64 ∏ ∏ PROPN cana-572 25 65 β€Š β€Š SPACE cana-572 25 66 𝑛 𝑛 PROPN cana-572 25 67 π‘–βˆ’1 π‘–βˆ’1 PROPN cana-572 25 68 𝑝𝑖 𝑝𝑖 NOUN cana-572 25 69 π‘¦π‘˜(1 π‘¦π‘˜(1 PROPN cana-572 25 70 βˆ’ βˆ’ PROPN cana-572 25 71 𝑝𝑖 𝑝𝑖 NOUN cana-572 25 72 ) ) PUNCT cana-572 25 73 1βˆ’π›½ 1βˆ’π›½ NUM cana-572 25 74 ( ( PUNCT cana-572 25 75 2 2 NUM cana-572 25 76 ) ) PUNCT cana-572 25 77 the the DET cana-572 25 78 log log NOUN cana-572 25 79 of of ADP cana-572 25 80 the the DET cana-572 25 81 likelihood likelihood NOUN cana-572 25 82 function function NOUN cana-572 25 83 , , PUNCT cana-572 25 84 which which PRON cana-572 25 85 is be AUX cana-572 25 86 often often ADV cana-572 25 87 used use VERB cana-572 25 88 because because SCONJ cana-572 25 89 it it PRON cana-572 25 90 is be AUX cana-572 25 91 simpler simple ADJ cana-572 25 92 to to PART cana-572 25 93 maximize maximize VERB cana-572 25 94 : : PUNCT cana-572 25 95 log log NOUN cana-572 25 96 𝐿(𝛽 𝐿(𝛽 PRON cana-572 25 97 ) ) PUNCT cana-572 25 98 = = PUNCT cana-572 26 1 βˆ‘ βˆ‘ PUNCT cana-572 26 2 β€Š β€Š SPACE cana-572 26 3 𝑛 𝑛 PRON cana-572 26 4 π‘–βˆ’1 π‘–βˆ’1 PROPN cana-572 27 1 [ [ X cana-572 27 2 𝑦𝑖log 𝑦𝑖log NOUN cana-572 27 3 𝑝𝑖 𝑝𝑖 NOUN cana-572 27 4 + + CCONJ cana-572 27 5 ( ( PUNCT cana-572 27 6 1 1 NUM cana-572 27 7 βˆ’ βˆ’ NOUN cana-572 27 8 𝑦𝑖)log 𝑦𝑖)log NOUN cana-572 27 9 ( ( PUNCT cana-572 27 10 1 1 NUM cana-572 27 11 βˆ’ βˆ’ NOUN cana-572 27 12 𝑝𝑖 𝑝𝑖 NOUN cana-572 27 13 ) ) PUNCT cana-572 27 14 ] ] PUNCT cana-572 27 15 ( ( PUNCT cana-572 27 16 3 3 X cana-572 27 17 ) ) PUNCT cana-572 27 18 the the DET cana-572 27 19 first first ADJ cana-572 27 20 derivative derivative NOUN cana-572 27 21 of of ADP cana-572 27 22 the the DET cana-572 27 23 log log NOUN cana-572 27 24 - - PUNCT cana-572 27 25 likelihood likelihood NOUN cana-572 27 26 function function NOUN cana-572 27 27 , , PUNCT cana-572 27 28 used use VERB cana-572 27 29 to to PART cana-572 27 30 find find VERB cana-572 27 31 the the DET cana-572 27 32 maximum maximum ADJ cana-572 27 33 likelihood likelihood NOUN cana-572 27 34 estimates estimate NOUN cana-572 27 35 : : PUNCT cana-572 27 36 𝑆(𝛽 𝑆(𝛽 X cana-572 27 37 ) ) PUNCT cana-572 27 38 = = PUNCT cana-572 27 39 βˆ‚log βˆ‚log X cana-572 27 40 𝐿(𝛽 𝐿(𝛽 NUM cana-572 27 41 ) ) PUNCT cana-572 27 42 βˆ‚π›½ βˆ‚π›½ PROPN cana-572 27 43 βˆ’ βˆ’ PROPN cana-572 27 44 βˆ‘ βˆ‘ INTJ cana-572 27 45 β€Š β€Š SPACE cana-572 27 46 𝑛 𝑛 PROPN cana-572 28 1 π‘–βˆ’1 π‘–βˆ’1 PROPN cana-572 28 2 π‘₯𝑖(𝑦𝑖 π‘₯𝑖(𝑦𝑖 NUM cana-572 28 3 βˆ’ βˆ’ PROPN cana-572 28 4 𝑝𝑖 𝑝𝑖 NOUN cana-572 28 5 ) ) PUNCT cana-572 28 6 ( ( PUNCT cana-572 28 7 4 4 X cana-572 28 8 ) ) PUNCT cana-572 28 9 the the DET cana-572 28 10 second second ADJ cana-572 28 11 derivative derivative NOUN cana-572 28 12 of of ADP cana-572 28 13 the the DET cana-572 28 14 log log NOUN cana-572 28 15 - - PUNCT cana-572 28 16 likelihood likelihood NOUN cana-572 28 17 function function NOUN cana-572 28 18 , , PUNCT cana-572 28 19 which which PRON cana-572 28 20 assesses assess VERB cana-572 28 21 the the DET cana-572 28 22 curvature curvature NOUN cana-572 28 23 of of ADP cana-572 28 24 the the DET cana-572 28 25 loglikelihood loglikelihood ADJ cana-572 28 26 surface surface NOUN cana-572 28 27 : : PUNCT cana-572 28 28 communications communication NOUN cana-572 28 29 on on ADP cana-572 28 30 applied apply VERB cana-572 28 31 nonlinear nonlinear ADJ cana-572 28 32 analysis analysis NOUN cana-572 28 33 issn issn NOUN cana-572 28 34 : : PUNCT cana-572 28 35 1074 1074 NUM cana-572 28 36 - - PUNCT cana-572 28 37 133x 133x NUM cana-572 28 38 vol vol NOUN cana-572 28 39 31 31 NUM cana-572 28 40 no no NOUN cana-572 28 41 . . NOUN cana-572 28 42 2 2 NUM cana-572 28 43 ( ( PUNCT cana-572 28 44 2024 2024 NUM cana-572 28 45 ) ) PUNCT cana-572 28 46 333 333 NUM cana-572 28 47 https://internationalpubls.com https://internationalpubls.com X cana-572 28 48 𝐻(𝛽 𝐻(𝛽 NUM cana-572 28 49 ) ) PUNCT cana-572 28 50 = = SYM cana-572 28 51 βˆ’ βˆ’ PROPN cana-572 28 52 βˆ‘ βˆ‘ INTJ cana-572 28 53 β€Š β€Š SPACE cana-572 28 54 𝑛 𝑛 PRON cana-572 28 55 π‘–βˆ’1 π‘–βˆ’1 PROPN cana-572 28 56 π‘₯𝑖π‘₯𝑖 π‘₯𝑖π‘₯𝑖 NOUN cana-572 28 57 𝑇𝑝𝑖(1 𝑇𝑝𝑖(1 VERB cana-572 28 58 βˆ’ βˆ’ PROPN cana-572 28 59 𝑝𝑖 𝑝𝑖 NOUN cana-572 28 60 ) ) PUNCT cana-572 28 61 ( ( PUNCT cana-572 28 62 5 5 X cana-572 28 63 ) ) PUNCT cana-572 28 64 the the DET cana-572 28 65 update update NOUN cana-572 28 66 rule rule NOUN cana-572 28 67 in in ADP cana-572 28 68 the the DET cana-572 28 69 newton newton PROPN cana-572 28 70 - - PUNCT cana-572 28 71 raphson raphson PROPN cana-572 28 72 method method NOUN cana-572 28 73 for for ADP cana-572 28 74 finding find VERB cana-572 28 75 the the DET cana-572 28 76 maximum maximum ADJ cana-572 28 77 likelihood likelihood NOUN cana-572 28 78 estimates estimate NOUN cana-572 28 79 : : PUNCT cana-572 28 80 𝛽(new 𝛽(new ADJ cana-572 28 81 ) ) PUNCT cana-572 28 82 βˆ’ βˆ’ PROPN cana-572 28 83 𝛽(old 𝛽(old PROPN cana-572 28 84 ) ) PUNCT cana-572 29 1 βˆ’ βˆ’ PROPN cana-572 29 2 π»βˆ’1(𝛽(old π»βˆ’1(𝛽(old NOUN cana-572 29 3 ) ) PUNCT cana-572 29 4 ) ) PUNCT cana-572 29 5 𝑆(𝛽(old 𝑆(𝛽(old PROPN cana-572 29 6 ) ) PUNCT cana-572 29 7 ) ) PUNCT cana-572 30 1 ( ( PUNCT cana-572 30 2 6 6 X cana-572 30 3 ) ) PUNCT cana-572 30 4 the the DET cana-572 30 5 variance variance NOUN cana-572 30 6 - - PUNCT cana-572 30 7 covariance covariance NOUN cana-572 30 8 matrix matrix NOUN cana-572 30 9 of of ADP cana-572 30 10 the the DET cana-572 30 11 estimator estimator NOUN cana-572 30 12 𝛽 𝛽 PROPN cana-572 30 13 , , PUNCT cana-572 30 14 assuming assume VERB cana-572 30 15 the the DET cana-572 30 16 model model NOUN cana-572 30 17 is be AUX cana-572 30 18 correctly correctly ADV cana-572 30 19 specified specify VERB cana-572 30 20 : : PUNCT cana-572 30 21 var var NOUN cana-572 30 22 ( ( PUNCT cana-572 30 23 οΏ½ οΏ½ NOUN cana-572 30 24 Μ‚ Μ‚ SYM cana-572 30 25 οΏ½ οΏ½ NOUN cana-572 30 26 ) ) PUNCT cana-572 30 27 = = SYM cana-572 30 28 βˆ’[𝐻( βˆ’[𝐻( PROPN cana-572 30 29 οΏ½ οΏ½ PROPN cana-572 30 30 Μ‚ Μ‚ NUM cana-572 30 31 οΏ½ οΏ½ NOUN cana-572 30 32 )]βˆ’1 )]βˆ’1 X cana-572 30 33 ( ( PUNCT cana-572 30 34 7 7 X cana-572 30 35 ) ) PUNCT cana-572 30 36 wald wald NOUN cana-572 30 37 test test NOUN cana-572 30 38 statistic statistic NOUN cana-572 30 39 is be AUX cana-572 30 40 used use VERB cana-572 30 41 for for ADP cana-572 30 42 hypothesis hypothesis NOUN cana-572 30 43 testing testing NOUN cana-572 30 44 of of ADP cana-572 30 45 coefficients coefficient NOUN cana-572 30 46 : : PUNCT cana-572 30 47 π‘Š π‘Š NOUN cana-572 30 48 = = SYM cana-572 30 49 ( ( PUNCT cana-572 30 50 οΏ½ οΏ½ PROPN cana-572 30 51 Μ‚ Μ‚ NOUN cana-572 30 52 οΏ½ οΏ½ NOUN cana-572 30 53 𝑗 𝑗 NOUN cana-572 30 54 βˆ’ βˆ’ PROPN cana-572 30 55 0 0 NUM cana-572 30 56 ) ) PUNCT cana-572 30 57 2 2 NUM cana-572 31 1 [ [ X cana-572 31 2 var var NOUN cana-572 31 3 ( ( PUNCT cana-572 31 4 οΏ½ οΏ½ NOUN cana-572 31 5 Μ‚ Μ‚ VERB cana-572 31 6 οΏ½ οΏ½ NOUN cana-572 31 7 𝑗 𝑗 NOUN cana-572 31 8 ) ) PUNCT cana-572 31 9 ] ] PUNCT cana-572 31 10 βˆ’1 βˆ’1 NOUN cana-572 31 11 ( ( PUNCT cana-572 31 12 8) 8) NUM cana-572 31 13 receiver receiver NOUN cana-572 31 14 operating operate VERB cana-572 31 15 characteristic characteristic NOUN cana-572 31 16 ( ( PUNCT cana-572 31 17 roc roc PROPN cana-572 31 18 ) ) PUNCT cana-572 31 19 curve curve NOUN cana-572 31 20 is be AUX cana-572 31 21 a a DET cana-572 31 22 tool tool NOUN cana-572 31 23 used use VERB cana-572 31 24 to to PART cana-572 31 25 evaluate evaluate VERB cana-572 31 26 the the DET cana-572 31 27 performance performance NOUN cana-572 31 28 of of ADP cana-572 31 29 a a DET cana-572 31 30 binary binary ADJ cana-572 31 31 classifier classifier NOUN cana-572 31 32 system system NOUN cana-572 31 33 : : PUNCT cana-572 31 34 tpr tpr X cana-572 31 35 = = PROPN cana-572 31 36 tp tp NOUN cana-572 31 37 tp tp ADP cana-572 31 38 + + CCONJ cana-572 31 39 in in ADP cana-572 31 40 ( ( PUNCT cana-572 31 41 9 9 NUM cana-572 31 42 ) ) PUNCT cana-572 31 43 fpr fpr NOUN cana-572 31 44 = = SYM cana-572 31 45 fp fp X cana-572 31 46 tn+ft tn+ft X cana-572 31 47 ( ( PUNCT cana-572 31 48 10 10 NUM cana-572 31 49 ) ) PUNCT cana-572 31 50 area area NOUN cana-572 31 51 under under ADP cana-572 31 52 the the DET cana-572 31 53 roc roc PROPN cana-572 31 54 curve curve NOUN cana-572 31 55 ( ( PUNCT cana-572 31 56 auc auc NOUN cana-572 31 57 ) ) PUNCT cana-572 31 58 is be AUX cana-572 31 59 a a DET cana-572 31 60 scalar scalar ADJ cana-572 31 61 measure measure NOUN cana-572 31 62 to to PART cana-572 31 63 assess assess VERB cana-572 31 64 the the DET cana-572 31 65 overall overall ADJ cana-572 31 66 performance performance NOUN cana-572 31 67 of of ADP cana-572 31 68 the the DET cana-572 31 69 diagnostic diagnostic ADJ cana-572 31 70 tests test NOUN cana-572 31 71 : : PUNCT cana-572 31 72 auc auc X cana-572 31 73 = = PUNCT cana-572 32 1 ∫ ∫ PROPN cana-572 32 2 β€Š β€Š SPACE cana-572 32 3 1 1 NUM cana-572 32 4 0 0 NUM cana-572 32 5 tpr(𝑑)𝑑𝑑 tpr(𝑑)𝑑𝑑 NOUN cana-572 32 6 ( ( PUNCT cana-572 32 7 11 11 NUM cana-572 32 8 ) ) PUNCT cana-572 32 9 k k ADJ cana-572 32 10 - - ADJ cana-572 32 11 fold fold ADJ cana-572 32 12 cross cross ADJ cana-572 32 13 - - ADJ cana-572 32 14 validation validation ADJ cana-572 32 15 procedure procedure NOUN cana-572 32 16 to to PART cana-572 32 17 evaluate evaluate VERB cana-572 32 18 model model NOUN cana-572 32 19 stability stability NOUN cana-572 32 20 : : PUNCT cana-572 32 21 𝐢𝑉kβˆ’ 𝐢𝑉kβˆ’ NOUN cana-572 32 22 fold fold NOUN cana-572 32 23 = = VERB cana-572 32 24 1 1 NUM cana-572 32 25 π‘˜ π‘˜ PRON cana-572 32 26 βˆ‘ βˆ‘ PROPN cana-572 32 27 β€Š β€Š SPACE cana-572 32 28 π‘˜ π‘˜ ADP cana-572 32 29 π‘–βˆ’1 π‘–βˆ’1 PROPN cana-572 32 30 accuracy accuracy NOUN cana-572 32 31 𝑖 𝑖 SYM cana-572 32 32 ( ( PUNCT cana-572 32 33 12 12 NUM cana-572 32 34 ) ) PUNCT cana-572 32 35 akaike akaike ADJ cana-572 32 36 information information NOUN cana-572 32 37 criterion criterion NOUN cana-572 32 38 ( ( PUNCT cana-572 32 39 aic aic PROPN cana-572 32 40 ) ) PUNCT cana-572 32 41 used use VERB cana-572 32 42 for for ADP cana-572 32 43 model model NOUN cana-572 32 44 selection selection NOUN cana-572 32 45 among among ADP cana-572 32 46 a a DET cana-572 32 47 set set NOUN cana-572 32 48 of of ADP cana-572 32 49 models model NOUN cana-572 32 50 : : PUNCT cana-572 32 51 aic aic PROPN cana-572 32 52 = = PROPN cana-572 33 1 2π‘˜ 2π‘˜ NUM cana-572 33 2 βˆ’ βˆ’ PROPN cana-572 33 3 2log 2log PROPN cana-572 33 4 ( ( PUNCT cana-572 33 5 𝐿 𝐿 PROPN cana-572 33 6 ) ) PUNCT cana-572 33 7 ( ( PUNCT cana-572 33 8 13 13 NUM cana-572 33 9 ) ) PUNCT cana-572 33 10 bayesian bayesian NOUN cana-572 33 11 information information NOUN cana-572 33 12 criterion criterion NOUN cana-572 33 13 ( ( PUNCT cana-572 33 14 bic bic PROPN cana-572 33 15 ) ) PUNCT cana-572 33 16 is be AUX cana-572 33 17 an an DET cana-572 33 18 another another DET cana-572 33 19 criterion criterion NOUN cana-572 33 20 for for ADP cana-572 33 21 model model NOUN cana-572 33 22 selection selection NOUN cana-572 33 23 : : PUNCT cana-572 33 24 bic bic PROPN cana-572 33 25 = = NOUN cana-572 33 26 log log PROPN cana-572 33 27 ( ( PUNCT cana-572 33 28 𝑛)π‘˜ 𝑛)π‘˜ PROPN cana-572 33 29 βˆ’ βˆ’ PROPN cana-572 33 30 2log 2log PROPN cana-572 33 31 ( ( PUNCT cana-572 33 32 𝐿 𝐿 PROPN cana-572 33 33 ) ) PUNCT cana-572 33 34 ( ( PUNCT cana-572 33 35 14 14 NUM cana-572 33 36 ) ) PUNCT cana-572 33 37 sensitivity sensitivity NOUN cana-572 33 38 analysis analysis NOUN cana-572 33 39 formula formula NOUN cana-572 33 40 is be AUX cana-572 33 41 used use VERB cana-572 33 42 to to PART cana-572 33 43 calculate calculate VERB cana-572 33 44 sensitivity sensitivity NOUN cana-572 33 45 , , PUNCT cana-572 33 46 or or CCONJ cana-572 33 47 true true ADJ cana-572 33 48 positive positive ADJ cana-572 33 49 rate rate NOUN cana-572 33 50 : : PUNCT cana-572 33 51 sensitivity sensitivity NOUN cana-572 33 52 = = SYM cana-572 33 53 𝑇𝑃 𝑇𝑃 PROPN cana-572 33 54 tp tp NOUN cana-572 33 55 + + NOUN cana-572 33 56 fn fn PROPN cana-572 33 57 ( ( PUNCT cana-572 33 58 15 15 NUM cana-572 33 59 ) ) PUNCT cana-572 33 60 specificity specificity NOUN cana-572 33 61 analysis analysis NOUN cana-572 33 62 is be AUX cana-572 33 63 used use VERB cana-572 33 64 to to PART cana-572 33 65 calculate calculate VERB cana-572 33 66 specificity specificity NOUN cana-572 33 67 , , PUNCT cana-572 33 68 or or CCONJ cana-572 33 69 true true ADJ cana-572 33 70 negative negative ADJ cana-572 33 71 rate rate NOUN cana-572 33 72 : : PUNCT cana-572 33 73 specificity= specificity= NUM cana-572 33 74 tn tn NOUN cana-572 33 75 tn+fn tn+fn X cana-572 33 76 ( ( PUNCT cana-572 33 77 16 16 NUM cana-572 33 78 ) ) PUNCT cana-572 33 79 positive positive ADJ cana-572 33 80 predictive predictive ADJ cana-572 33 81 value value NOUN cana-572 33 82 is be AUX cana-572 33 83 the the DET cana-572 33 84 probability probability NOUN cana-572 33 85 that that SCONJ cana-572 33 86 subjects subject NOUN cana-572 33 87 with with ADP cana-572 33 88 a a DET cana-572 33 89 positive positive ADJ cana-572 33 90 screening screening NOUN cana-572 33 91 test test NOUN cana-572 33 92 truly truly ADV cana-572 33 93 have have AUX cana-572 33 94 the the DET cana-572 33 95 disease disease NOUN cana-572 33 96 : : PUNCT cana-572 33 97 ppv ppv NOUN cana-572 33 98 = = PUNCT cana-572 33 99 tp tp X cana-572 33 100 tp+fp tp+fp NUM cana-572 33 101 ( ( PUNCT cana-572 33 102 17 17 NUM cana-572 33 103 ) ) PUNCT cana-572 33 104 negative negative ADJ cana-572 33 105 predictive predictive ADJ cana-572 33 106 value value NOUN cana-572 33 107 is be AUX cana-572 33 108 the the DET cana-572 33 109 probability probability NOUN cana-572 33 110 that that SCONJ cana-572 33 111 subjects subject NOUN cana-572 33 112 with with ADP cana-572 33 113 a a DET cana-572 33 114 negative negative ADJ cana-572 33 115 screening screening NOUN cana-572 33 116 test test NOUN cana-572 33 117 truly truly ADV cana-572 33 118 do do AUX cana-572 33 119 n't not PART cana-572 33 120 have have AUX cana-572 33 121 the the DET cana-572 33 122 disease disease NOUN cana-572 33 123 : : PUNCT cana-572 33 124 npv npv NOUN cana-572 33 125 = = SYM cana-572 33 126 tn tn PROPN cana-572 33 127 tn+fn tn+fn X cana-572 33 128 ( ( PUNCT cana-572 33 129 18 18 NUM cana-572 33 130 ) ) PUNCT cana-572 33 131 communications communication NOUN cana-572 33 132 on on ADP cana-572 33 133 applied apply VERB cana-572 33 134 nonlinear nonlinear ADJ cana-572 33 135 analysis analysis NOUN cana-572 33 136 issn issn NOUN cana-572 33 137 : : PUNCT cana-572 33 138 1074 1074 NUM cana-572 33 139 - - PUNCT cana-572 33 140 133x 133x NUM cana-572 33 141 vol vol NOUN cana-572 33 142 31 31 NUM cana-572 33 143 no no NOUN cana-572 33 144 . . NOUN cana-572 33 145 2 2 NUM cana-572 33 146 ( ( PUNCT cana-572 33 147 2024 2024 NUM cana-572 33 148 ) ) PUNCT cana-572 33 149 334 334 NUM cana-572 33 150 https://internationalpubls.com https://internationalpubls.com X cana-572 33 151 f1score f1score NOUN cana-572 33 152 is be AUX cana-572 33 153 equal equal ADJ cana-572 33 154 to to ADP cana-572 33 155 the the DET cana-572 33 156 harmonic harmonic ADJ cana-572 33 157 mean mean NOUN cana-572 33 158 of of ADP cana-572 33 159 precision precision NOUN cana-572 33 160 and and CCONJ cana-572 33 161 recall recall NOUN cana-572 33 162 : : PUNCT cana-572 33 163 𝐹1 𝐹1 PROPN cana-572 33 164 = = NOUN cana-572 33 165 2 2 NUM cana-572 33 166 β‹… β‹… NOUN cana-572 33 167 ppv.sensitivity ppv.sensitivity NOUN cana-572 33 168 ppv ppv NOUN cana-572 33 169 + + CCONJ cana-572 33 170 sensitivity sensitivity NOUN cana-572 33 171 ( ( PUNCT cana-572 33 172 19 19 NUM cana-572 33 173 ) ) PUNCT cana-572 33 174 decision decision NOUN cana-572 33 175 tree tree NOUN cana-572 33 176 split split NOUN cana-572 33 177 criterion criterion NOUN cana-572 33 178 is be AUX cana-572 33 179 used use VERB cana-572 33 180 in in ADP cana-572 33 181 decision decision NOUN cana-572 33 182 tree tree NOUN cana-572 33 183 algorithms algorithm NOUN cana-572 33 184 to to PART cana-572 33 185 choose choose VERB cana-572 33 186 the the DET cana-572 33 187 best good ADJ cana-572 33 188 split split NOUN cana-572 33 189 : : PUNCT cana-572 33 190 𝐺 𝐺 NOUN cana-572 34 1 βˆ’ βˆ’ PROPN cana-572 34 2 1 1 NUM cana-572 34 3 βˆ’ βˆ’ PROPN cana-572 34 4 βˆ‘ βˆ‘ PROPN cana-572 34 5 β€Š β€Š SPACE cana-572 34 6 𝑐 𝑐 PROPN cana-572 34 7 π‘–βˆ’1 π‘–βˆ’1 PROPN cana-572 34 8 𝑝𝑖 𝑝𝑖 PROPN cana-572 34 9 2 2 NUM cana-572 34 10 ( ( PUNCT cana-572 34 11 20 20 NUM cana-572 34 12 ) ) PUNCT cana-572 34 13 information information NOUN cana-572 34 14 gain gain NOUN cana-572 34 15 is be AUX cana-572 34 16 used use VERB cana-572 34 17 in in ADP cana-572 34 18 decision decision NOUN cana-572 34 19 tree tree NOUN cana-572 34 20 algorithms algorithm NOUN cana-572 34 21 , , PUNCT cana-572 34 22 measuring measure VERB cana-572 34 23 the the DET cana-572 34 24 effectiveness effectiveness NOUN cana-572 34 25 of of ADP cana-572 34 26 an an DET cana-572 34 27 attribute attribute NOUN cana-572 34 28 in in ADP cana-572 34 29 classifying classify VERB cana-572 34 30 the the DET cana-572 34 31 training training NOUN cana-572 34 32 data data NOUN cana-572 34 33 : : PUNCT cana-572 34 34 𝐼𝐺(𝑇 𝐼𝐺(𝑇 NOUN cana-572 34 35 , , PUNCT cana-572 34 36 𝐴 𝐴 PROPN cana-572 34 37 ) ) PUNCT cana-572 34 38 = = PUNCT cana-572 35 1 𝐻(𝑇 𝐻(𝑇 X cana-572 35 2 ) ) PUNCT cana-572 35 3 βˆ’ βˆ’ PROPN cana-572 35 4 𝐻(𝑇 𝐻(𝑇 PROPN cana-572 35 5 ∣ ∣ PROPN cana-572 35 6 𝐴 𝐴 PROPN cana-572 35 7 ) ) PUNCT cana-572 35 8 ( ( PUNCT cana-572 35 9 21 21 NUM cana-572 35 10 ) ) PUNCT cana-572 35 11 entropy entropy NOUN cana-572 35 12 which which PRON cana-572 35 13 is be AUX cana-572 35 14 a a DET cana-572 35 15 measure measure NOUN cana-572 35 16 of of ADP cana-572 35 17 the the DET cana-572 35 18 amount amount NOUN cana-572 35 19 of of ADP cana-572 35 20 uncertainty uncertainty NOUN cana-572 35 21 in in ADP cana-572 35 22 the the DET cana-572 35 23 dataset dataset ADJ cana-572 35 24 𝑇 𝑇 PROPN cana-572 35 25 : : PUNCT cana-572 35 26 𝐻(𝑇 𝐻(𝑇 NUM cana-572 35 27 ) ) PUNCT cana-572 35 28 = = SYM cana-572 36 1 βˆ’ βˆ’ PROPN cana-572 36 2 βˆ‘ βˆ‘ PUNCT cana-572 36 3 β€Š β€Š SPACE cana-572 36 4 𝑐 𝑐 PROPN cana-572 36 5 π‘–βˆ’1 π‘–βˆ’1 PROPN cana-572 36 6 𝑝𝑖log2 𝑝𝑖log2 NOUN cana-572 36 7 ( ( PUNCT cana-572 36 8 𝑝𝑖 𝑝𝑖 NOUN cana-572 36 9 ) ) PUNCT cana-572 36 10 ( ( PUNCT cana-572 36 11 22 22 X cana-572 36 12 ) ) PUNCT cana-572 36 13 conditional conditional ADJ cana-572 36 14 entropy entropy NOUN cana-572 36 15 is be AUX cana-572 36 16 equal equal ADJ cana-572 36 17 to to ADP cana-572 36 18 entropy entropy NOUN cana-572 36 19 of of ADP cana-572 36 20 the the DET cana-572 36 21 dataset dataset NOUN cana-572 36 22 after after ADP cana-572 36 23 using use VERB cana-572 36 24 attribute attribute NOUN cana-572 36 25 𝐴 𝐴 PROPN cana-572 36 26 for for ADP cana-572 36 27 splitting splitting NOUN cana-572 36 28 : : PUNCT cana-572 36 29 𝐻(𝑇 𝐻(𝑇 NUM cana-572 36 30 ∣ ∣ PROPN cana-572 36 31 𝐴 𝐴 PROPN cana-572 36 32 ) ) PUNCT cana-572 36 33 = = PUNCT cana-572 37 1 βˆ‘ βˆ‘ PUNCT cana-572 37 2 β€Š β€Š SPACE cana-572 37 3 𝑣 𝑣 PRON cana-572 37 4 π‘—βˆ’1 π‘—βˆ’1 PROPN cana-572 37 5 |𝑇𝑗| |𝑇𝑗| PROPN cana-572 37 6 |𝑇| |𝑇| PROPN cana-572 37 7 𝐻(𝑇𝑗 𝐻(𝑇𝑗 PROPN cana-572 37 8 ) ) PUNCT cana-572 37 9 ( ( PUNCT cana-572 37 10 23 23 X cana-572 37 11 ) ) PUNCT cana-572 37 12 support support NOUN cana-572 37 13 vector vector NOUN cana-572 37 14 machine machine NOUN cana-572 37 15 margin margin NOUN cana-572 37 16 maximization maximization NOUN cana-572 37 17 of of ADP cana-572 37 18 the the DET cana-572 37 19 objective objective ADJ cana-572 37 20 function function NOUN cana-572 37 21 for for ADP cana-572 37 22 svm svm NOUN cana-572 37 23 focusing focus VERB cana-572 37 24 on on ADP cana-572 37 25 margin margin NOUN cana-572 37 26 maximization maximization NOUN cana-572 37 27 : : PUNCT cana-572 37 28 min min PROPN cana-572 37 29 𝐰,𝑏 𝐰,𝑏 NOUN cana-572 37 30 β€Š β€Š SPACE cana-572 38 1 1 1 NUM cana-572 38 2 2 2 NUM cana-572 38 3 βˆ₯ βˆ₯ NUM cana-572 38 4 𝐰 𝐰 X cana-572 38 5 βˆ₯2 βˆ₯2 NOUN cana-572 38 6 ( ( PUNCT cana-572 38 7 24 24 NUM cana-572 38 8 ) ) PUNCT cana-572 38 9 kernel kernel NOUN cana-572 38 10 trick trick NOUN cana-572 38 11 for for ADP cana-572 38 12 non non ADJ cana-572 38 13 - - ADJ cana-572 38 14 linear linear ADJ cana-572 38 15 separation separation NOUN cana-572 38 16 is be AUX cana-572 38 17 a a DET cana-572 38 18 transformation transformation NOUN cana-572 38 19 used use VERB cana-572 38 20 in in ADP cana-572 38 21 svm svm PROPN cana-572 38 22 for for ADP cana-572 38 23 non non ADJ cana-572 38 24 - - ADJ cana-572 38 25 linear linear ADJ cana-572 38 26 classification classification NOUN cana-572 38 27 : : PUNCT cana-572 38 28 𝐾(π‘₯𝑖 𝐾(π‘₯𝑖 ADJ cana-572 38 29 , , PUNCT cana-572 38 30 π‘₯𝑗 π‘₯𝑗 PROPN cana-572 38 31 ) ) PUNCT cana-572 38 32 = = SYM cana-572 38 33 πœ™(π‘₯𝑖 πœ™(π‘₯𝑖 ADJ cana-572 38 34 ) ) PUNCT cana-572 38 35 π‘‡πœ™(π‘₯𝑗 π‘‡πœ™(π‘₯𝑗 NOUN cana-572 38 36 ) ) PUNCT cana-572 38 37 ( ( PUNCT cana-572 38 38 25 25 NUM cana-572 38 39 ) ) PUNCT cana-572 38 40 after after ADP cana-572 38 41 establishing establish VERB cana-572 38 42 the the DET cana-572 38 43 mathematical mathematical ADJ cana-572 38 44 framework framework NOUN cana-572 38 45 , , PUNCT cana-572 38 46 it it PRON cana-572 38 47 ’s ’ VERB cana-572 38 48 crucial crucial ADJ cana-572 38 49 to to PART cana-572 38 50 understand understand VERB cana-572 38 51 the the DET cana-572 38 52 implications implication NOUN cana-572 38 53 of of ADP cana-572 38 54 these these DET cana-572 38 55 equations equation NOUN cana-572 38 56 and and CCONJ cana-572 38 57 how how SCONJ cana-572 38 58 they they PRON cana-572 38 59 can can AUX cana-572 38 60 be be AUX cana-572 38 61 practically practically ADV cana-572 38 62 applied apply VERB cana-572 38 63 in in ADP cana-572 38 64 the the DET cana-572 38 65 field field NOUN cana-572 38 66 of of ADP cana-572 38 67 breast breast NOUN cana-572 38 68 cancer cancer NOUN cana-572 38 69 prediction prediction NOUN cana-572 38 70 . . PUNCT cana-572 39 1 each each DET cana-572 39 2 equation equation NOUN cana-572 39 3 plays play VERB cana-572 39 4 a a DET cana-572 39 5 critical critical ADJ cana-572 39 6 role role NOUN cana-572 39 7 in in ADP cana-572 39 8 enhancing enhance VERB cana-572 39 9 the the DET cana-572 39 10 robustness robustness NOUN cana-572 39 11 and and CCONJ cana-572 39 12 accuracy accuracy NOUN cana-572 39 13 of of ADP cana-572 39 14 predictive predictive ADJ cana-572 39 15 models model NOUN cana-572 39 16 . . PUNCT cana-572 40 1 the the DET cana-572 40 2 logistic logistic ADJ cana-572 40 3 regression regression NOUN cana-572 40 4 model model NOUN cana-572 40 5 , , PUNCT cana-572 40 6 for for ADP cana-572 40 7 instance instance NOUN cana-572 40 8 , , PUNCT cana-572 40 9 is be AUX cana-572 40 10 foundational foundational ADJ cana-572 40 11 in in ADP cana-572 40 12 medical medical ADJ cana-572 40 13 statistics statistic NOUN cana-572 40 14 , , PUNCT cana-572 40 15 allowing allow VERB cana-572 40 16 for for ADP cana-572 40 17 the the DET cana-572 40 18 estimation estimation NOUN cana-572 40 19 of of ADP cana-572 40 20 probabilities probability NOUN cana-572 40 21 directly directly ADV cana-572 40 22 linked link VERB cana-572 40 23 to to ADP cana-572 40 24 patient patient ADJ cana-572 40 25 outcomes outcome NOUN cana-572 40 26 based base VERB cana-572 40 27 on on ADP cana-572 40 28 multiple multiple ADJ cana-572 40 29 risk risk NOUN cana-572 40 30 factors factor NOUN cana-572 40 31 . . PUNCT cana-572 41 1 the the DET cana-572 41 2 optimization optimization NOUN cana-572 41 3 of of ADP cana-572 41 4 this this DET cana-572 41 5 model model NOUN cana-572 41 6 through through ADP cana-572 41 7 operational operational ADJ cana-572 41 8 research research NOUN cana-572 41 9 techniques technique NOUN cana-572 41 10 , , PUNCT cana-572 41 11 such such ADJ cana-572 41 12 as as ADP cana-572 41 13 the the DET cana-572 41 14 newton newton PROPN cana-572 41 15 - - PUNCT cana-572 41 16 raphson raphson PROPN cana-572 41 17 method method NOUN cana-572 41 18 ( ( PUNCT cana-572 41 19 equation equation NOUN cana-572 41 20 1.6 1.6 NUM cana-572 41 21 ) ) PUNCT cana-572 41 22 , , PUNCT cana-572 41 23 significantly significantly ADV cana-572 41 24 refines refine VERB cana-572 41 25 parameter parameter NOUN cana-572 41 26 estimation estimation NOUN cana-572 41 27 , , PUNCT cana-572 41 28 making make VERB cana-572 41 29 the the DET cana-572 41 30 model model NOUN cana-572 41 31 more more ADV cana-572 41 32 responsive responsive ADJ cana-572 41 33 to to ADP cana-572 41 34 subtle subtle ADJ cana-572 41 35 variations variation NOUN cana-572 41 36 in in ADP cana-572 41 37 patient patient ADJ cana-572 41 38 data datum NOUN cana-572 41 39 . . PUNCT cana-572 42 1 the the DET cana-572 42 2 hessian hessian ADJ cana-572 42 3 matrix matrix NOUN cana-572 42 4 and and CCONJ cana-572 42 5 variance variance NOUN cana-572 42 6 - - PUNCT cana-572 42 7 covariance covariance NOUN cana-572 42 8 calculations calculation NOUN cana-572 42 9 are be AUX cana-572 42 10 critical critical ADJ cana-572 42 11 for for ADP cana-572 42 12 understanding understand VERB cana-572 42 13 the the DET cana-572 42 14 confidence confidence NOUN cana-572 42 15 intervals interval NOUN cana-572 42 16 around around ADP cana-572 42 17 estimated estimate VERB cana-572 42 18 parameters parameter NOUN cana-572 42 19 , , PUNCT cana-572 42 20 providing provide VERB cana-572 42 21 insights insight NOUN cana-572 42 22 into into ADP cana-572 42 23 the the DET cana-572 42 24 reliability reliability NOUN cana-572 42 25 of of ADP cana-572 42 26 predictions prediction NOUN cana-572 42 27 and and CCONJ cana-572 42 28 the the DET cana-572 42 29 stability stability NOUN cana-572 42 30 of of ADP cana-572 42 31 the the DET cana-572 42 32 model model NOUN cana-572 42 33 under under ADP cana-572 42 34 various various ADJ cana-572 42 35 conditions condition NOUN cana-572 42 36 . . PUNCT cana-572 43 1 performance performance NOUN cana-572 43 2 metrics metric NOUN cana-572 43 3 derived derive VERB cana-572 43 4 from from ADP cana-572 43 5 statistical statistical ADJ cana-572 43 6 analysis analysis NOUN cana-572 43 7 , , PUNCT cana-572 43 8 such such ADJ cana-572 43 9 as as ADP cana-572 43 10 the the DET cana-572 43 11 auc auc NOUN cana-572 43 12 of of ADP cana-572 43 13 the the DET cana-572 43 14 roc roc PROPN cana-572 43 15 curve curve NOUN cana-572 43 16 , , PUNCT cana-572 43 17 are be AUX cana-572 43 18 indispensable indispensable ADJ cana-572 43 19 for for ADP cana-572 43 20 evaluating evaluate VERB cana-572 43 21 the the DET cana-572 43 22 effectiveness effectiveness NOUN cana-572 43 23 of of ADP cana-572 43 24 breast breast NOUN cana-572 43 25 cancer cancer NOUN cana-572 43 26 prediction prediction NOUN cana-572 43 27 models model NOUN cana-572 43 28 . . PUNCT cana-572 44 1 they they PRON cana-572 44 2 help help VERB cana-572 44 3 in in ADP cana-572 44 4 assessing assess VERB cana-572 44 5 how how SCONJ cana-572 44 6 well well ADV cana-572 44 7 the the DET cana-572 44 8 model model NOUN cana-572 44 9 can can AUX cana-572 44 10 distinguish distinguish VERB cana-572 44 11 between between ADP cana-572 44 12 patients patient NOUN cana-572 44 13 with with ADP cana-572 44 14 and and CCONJ cana-572 44 15 without without ADP cana-572 44 16 breast breast NOUN cana-572 44 17 cancer cancer NOUN cana-572 44 18 , , PUNCT cana-572 44 19 which which PRON cana-572 44 20 is be AUX cana-572 44 21 crucial crucial ADJ cana-572 44 22 for for ADP cana-572 44 23 clinical clinical ADJ cana-572 44 24 decision decision NOUN cana-572 44 25 - - PUNCT cana-572 44 26 making making NOUN cana-572 44 27 . . PUNCT cana-572 45 1 communications communication NOUN cana-572 45 2 on on ADP cana-572 45 3 applied apply VERB cana-572 45 4 nonlinear nonlinear ADJ cana-572 45 5 analysis analysis NOUN cana-572 45 6 issn issn NOUN cana-572 45 7 : : PUNCT cana-572 45 8 1074 1074 NUM cana-572 45 9 - - PUNCT cana-572 45 10 133x 133x NUM cana-572 45 11 vol vol NOUN cana-572 45 12 31 31 NUM cana-572 45 13 no no NOUN cana-572 45 14 . . NOUN cana-572 45 15 2 2 NUM cana-572 45 16 ( ( PUNCT cana-572 45 17 2024 2024 NUM cana-572 45 18 ) ) PUNCT cana-572 45 19 335 335 NUM cana-572 45 20 https://internationalpubls.com https://internationalpubls.com X cana-572 46 1 moreover moreover ADV cana-572 46 2 , , PUNCT cana-572 46 3 cross cross ADJ cana-572 46 4 - - ADJ cana-572 46 5 validation validation ADJ cana-572 46 6 techniques technique NOUN cana-572 46 7 ensure ensure VERB cana-572 46 8 that that SCONJ cana-572 46 9 the the DET cana-572 46 10 model model NOUN cana-572 46 11 is be AUX cana-572 46 12 not not PART cana-572 46 13 just just ADV cana-572 46 14 fitting fit VERB cana-572 46 15 the the DET cana-572 46 16 data datum NOUN cana-572 46 17 well well ADV cana-572 46 18 but but CCONJ cana-572 46 19 also also ADV cana-572 46 20 generalizes generalize VERB cana-572 46 21 effectively effectively ADV cana-572 46 22 to to ADP cana-572 46 23 new new ADJ cana-572 46 24 , , PUNCT cana-572 46 25 unseen unseen ADJ cana-572 46 26 data datum NOUN cana-572 46 27 , , PUNCT cana-572 46 28 thus thus ADV cana-572 46 29 preventing prevent VERB cana-572 46 30 overfitting overfitting NOUN cana-572 46 31 . . PUNCT cana-572 47 1 this this PRON cana-572 47 2 is be AUX cana-572 47 3 particularly particularly ADV cana-572 47 4 important important ADJ cana-572 47 5 in in ADP cana-572 47 6 medical medical ADJ cana-572 47 7 applications application NOUN cana-572 47 8 where where SCONJ cana-572 47 9 the the DET cana-572 47 10 cost cost NOUN cana-572 47 11 of of ADP cana-572 47 12 a a DET cana-572 47 13 wrong wrong ADJ cana-572 47 14 prediction prediction NOUN cana-572 47 15 can can AUX cana-572 47 16 be be AUX cana-572 47 17 very very ADV cana-572 47 18 high high ADJ cana-572 47 19 . . PUNCT cana-572 48 1 finally finally ADV cana-572 48 2 , , PUNCT cana-572 48 3 advanced advanced ADJ cana-572 48 4 machine machine NOUN cana-572 48 5 learning learn VERB cana-572 48 6 techniques technique NOUN cana-572 48 7 such such ADJ cana-572 48 8 as as ADP cana-572 48 9 support support NOUN cana-572 48 10 vector vector NOUN cana-572 48 11 machines machine NOUN cana-572 48 12 and and CCONJ cana-572 48 13 decision decision NOUN cana-572 48 14 trees tree NOUN cana-572 48 15 utilize utilize VERB cana-572 48 16 operational operational ADJ cana-572 48 17 research research NOUN cana-572 48 18 and and CCONJ cana-572 48 19 statistical statistical ADJ cana-572 48 20 methods method NOUN cana-572 48 21 to to PART cana-572 48 22 find find VERB cana-572 48 23 non non ADJ cana-572 48 24 - - ADJ cana-572 48 25 linear linear ADJ cana-572 48 26 patterns pattern NOUN cana-572 48 27 and and CCONJ cana-572 48 28 complex complex ADJ cana-572 48 29 relationships relationship NOUN cana-572 48 30 in in ADP cana-572 48 31 data datum NOUN cana-572 48 32 that that PRON cana-572 48 33 might might AUX cana-572 48 34 not not PART cana-572 48 35 be be AUX cana-572 48 36 apparent apparent ADJ cana-572 48 37 through through ADP cana-572 48 38 traditional traditional ADJ cana-572 48 39 statistical statistical ADJ cana-572 48 40 methods method NOUN cana-572 48 41 alone alone ADV cana-572 48 42 . . PUNCT cana-572 49 1 in in ADP cana-572 49 2 conclusion conclusion NOUN cana-572 49 3 , , PUNCT cana-572 49 4 the the DET cana-572 49 5 integration integration NOUN cana-572 49 6 of of ADP cana-572 49 7 operational operational ADJ cana-572 49 8 research research NOUN cana-572 49 9 and and CCONJ cana-572 49 10 advanced advanced ADJ cana-572 49 11 statistical statistical ADJ cana-572 49 12 methods method NOUN cana-572 49 13 into into ADP cana-572 49 14 machine machine NOUN cana-572 49 15 learning learning NOUN cana-572 49 16 creates create VERB cana-572 49 17 a a DET cana-572 49 18 powerful powerful ADJ cana-572 49 19 tool tool NOUN cana-572 49 20 for for ADP cana-572 49 21 predicting predict VERB cana-572 49 22 breast breast NOUN cana-572 49 23 cancer cancer NOUN cana-572 49 24 . . PUNCT cana-572 50 1 this this DET cana-572 50 2 integrated integrate VERB cana-572 50 3 approach approach NOUN cana-572 50 4 not not PART cana-572 50 5 only only ADV cana-572 50 6 improves improve VERB cana-572 50 7 the the DET cana-572 50 8 accuracy accuracy NOUN cana-572 50 9 and and CCONJ cana-572 50 10 efficiency efficiency NOUN cana-572 50 11 of of ADP cana-572 50 12 predictions prediction NOUN cana-572 50 13 but but CCONJ cana-572 50 14 also also ADV cana-572 50 15 offers offer VERB cana-572 50 16 a a DET cana-572 50 17 deeper deep ADJ cana-572 50 18 understanding understanding NOUN cana-572 50 19 of of ADP cana-572 50 20 the the DET cana-572 50 21 underlying underlie VERB cana-572 50 22 patterns pattern NOUN cana-572 50 23 and and CCONJ cana-572 50 24 relationships relationship NOUN cana-572 50 25 in in ADP cana-572 50 26 medical medical ADJ cana-572 50 27 data datum NOUN cana-572 50 28 . . PUNCT cana-572 51 1 as as SCONJ cana-572 51 2 research research NOUN cana-572 51 3 progresses progress NOUN cana-572 51 4 , , PUNCT cana-572 51 5 these these DET cana-572 51 6 methods method NOUN cana-572 51 7 will will AUX cana-572 51 8 continue continue VERB cana-572 51 9 to to PART cana-572 51 10 evolve evolve VERB cana-572 51 11 , , PUNCT cana-572 51 12 providing provide VERB cana-572 51 13 ever ever ADV cana-572 51 14 more more ADV cana-572 51 15 sophisticated sophisticated ADJ cana-572 51 16 tools tool NOUN cana-572 51 17 that that PRON cana-572 51 18 can can AUX cana-572 51 19 be be AUX cana-572 51 20 used use VERB cana-572 51 21 to to PART cana-572 51 22 fight fight VERB cana-572 51 23 breast breast NOUN cana-572 51 24 cancer cancer NOUN cana-572 51 25 more more ADV cana-572 51 26 effectively effectively ADV cana-572 51 27 . . PUNCT cana-572 52 1 this this DET cana-572 52 2 ongoing ongoing ADJ cana-572 52 3 development development NOUN cana-572 52 4 underscores underscore VERB cana-572 52 5 the the DET cana-572 52 6 importance importance NOUN cana-572 52 7 of of ADP cana-572 52 8 interdisciplinary interdisciplinary ADJ cana-572 52 9 approaches approach NOUN cana-572 52 10 in in ADP cana-572 52 11 medical medical ADJ cana-572 52 12 research research NOUN cana-572 52 13 , , PUNCT cana-572 52 14 leveraging leverage VERB cana-572 52 15 the the DET cana-572 52 16 strengths strength NOUN cana-572 52 17 of of ADP cana-572 52 18 each each DET cana-572 52 19 field field NOUN cana-572 52 20 to to PART cana-572 52 21 tackle tackle VERB cana-572 52 22 complex complex ADJ cana-572 52 23 health health NOUN cana-572 52 24 challenges challenge NOUN cana-572 52 25 2 2 NUM cana-572 52 26 . . PUNCT cana-572 52 27 related relate VERB cana-572 52 28 study study NOUN cana-572 52 29 in in ADP cana-572 52 30 fact fact NOUN cana-572 52 31 , , PUNCT cana-572 52 32 breast breast NOUN cana-572 52 33 cancer cancer NOUN cana-572 52 34 has have AUX cana-572 52 35 been be AUX cana-572 52 36 recognized recognize VERB cana-572 52 37 as as ADP cana-572 52 38 the the DET cana-572 52 39 fifth fifth ADV cana-572 52 40 largest large ADJ cana-572 52 41 cause cause NOUN cana-572 52 42 of of ADP cana-572 52 43 cancer cancer NOUN cana-572 52 44 - - PUNCT cana-572 52 45 related relate VERB cana-572 52 46 death death NOUN cana-572 52 47 worldwide worldwide ADV cana-572 52 48 in in ADP cana-572 52 49 2020 2020 NUM cana-572 52 50 [ [ X cana-572 52 51 1 1 NUM cana-572 52 52 ] ] PUNCT cana-572 52 53 . . PUNCT cana-572 53 1 breast breast NOUN cana-572 53 2 cancer cancer NOUN cana-572 53 3 is be AUX cana-572 53 4 the the DET cana-572 53 5 most most ADV cana-572 53 6 often often ADV cana-572 53 7 diagnosed diagnose VERB cana-572 53 8 form form NOUN cana-572 53 9 of of ADP cana-572 53 10 cancer cancer NOUN cana-572 53 11 overall overall NOUN cana-572 53 12 and and CCONJ cana-572 53 13 among among ADP cana-572 53 14 women woman NOUN cana-572 53 15 all all ADV cana-572 53 16 over over ADP cana-572 53 17 the the DET cana-572 53 18 world world NOUN cana-572 53 19 . . PUNCT cana-572 54 1 on on ADP cana-572 54 2 a a DET cana-572 54 3 global global ADJ cana-572 54 4 scale scale NOUN cana-572 54 5 , , PUNCT cana-572 54 6 it it PRON cana-572 54 7 is be AUX cana-572 54 8 believed believe VERB cana-572 54 9 to to PART cana-572 54 10 be be AUX cana-572 54 11 the the DET cana-572 54 12 most most ADV cana-572 54 13 frequent frequent ADJ cana-572 54 14 kind kind NOUN cana-572 54 15 of of ADP cana-572 54 16 cancer cancer NOUN cana-572 55 1 [ [ X cana-572 55 2 2 2 NUM cana-572 55 3 ] ] PUNCT cana-572 55 4 . . PUNCT cana-572 56 1 there there PRON cana-572 56 2 are be VERB cana-572 56 3 a a DET cana-572 56 4 number number NOUN cana-572 56 5 of of ADP cana-572 56 6 different different ADJ cana-572 56 7 tests test NOUN cana-572 56 8 that that PRON cana-572 56 9 are be AUX cana-572 56 10 utilized utilize VERB cana-572 56 11 in in ADP cana-572 56 12 the the DET cana-572 56 13 process process NOUN cana-572 56 14 of of ADP cana-572 56 15 screening screen VERB cana-572 56 16 for for ADP cana-572 56 17 breast breast NOUN cana-572 56 18 cancer cancer NOUN cana-572 56 19 and and CCONJ cana-572 56 20 diagnosing diagnose VERB cana-572 56 21 the the DET cana-572 56 22 disease disease NOUN cana-572 56 23 . . PUNCT cana-572 57 1 these these DET cana-572 57 2 tests test NOUN cana-572 57 3 include include VERB cana-572 57 4 mammography mammography NOUN cana-572 57 5 , , PUNCT cana-572 57 6 breast breast NOUN cana-572 57 7 inspection inspection NOUN cana-572 57 8 , , PUNCT cana-572 57 9 and and CCONJ cana-572 57 10 a a DET cana-572 57 11 biopsy biopsy NOUN cana-572 57 12 . . PUNCT cana-572 58 1 the the DET cana-572 58 2 identification identification NOUN cana-572 58 3 of of ADP cana-572 58 4 breast breast NOUN cana-572 58 5 cancer cancer NOUN cana-572 58 6 has have AUX cana-572 58 7 been be AUX cana-572 58 8 accomplished accomplish VERB cana-572 58 9 by by ADP cana-572 58 10 the the DET cana-572 58 11 utilization utilization NOUN cana-572 58 12 of of ADP cana-572 58 13 a a DET cana-572 58 14 variety variety NOUN cana-572 58 15 of of ADP cana-572 58 16 imaging imaging NOUN cana-572 58 17 modalities modality NOUN cana-572 58 18 , , PUNCT cana-572 58 19 including include VERB cana-572 58 20 mammography mammography NOUN cana-572 58 21 , , PUNCT cana-572 58 22 ultrasound ultrasound NOUN cana-572 58 23 ( ( PUNCT cana-572 58 24 us us PROPN cana-572 58 25 ) ) PUNCT cana-572 58 26 , , PUNCT cana-572 58 27 magnetic magnetic ADJ cana-572 58 28 resonance resonance NOUN cana-572 58 29 imaging imaging NOUN cana-572 58 30 ( ( PUNCT cana-572 58 31 mri mri NOUN cana-572 58 32 ) ) PUNCT cana-572 58 33 , , PUNCT cana-572 58 34 histology histology NOUN cana-572 58 35 pictures picture NOUN cana-572 58 36 , , PUNCT cana-572 58 37 and and CCONJ cana-572 58 38 infrared infrared ADJ cana-572 58 39 thermography thermography NOUN cana-572 58 40 . . PUNCT cana-572 59 1 for for ADP cana-572 59 2 the the DET cana-572 59 3 screening screening NOUN cana-572 59 4 of of ADP cana-572 59 5 breast breast NOUN cana-572 59 6 cancer cancer NOUN cana-572 59 7 , , PUNCT cana-572 59 8 mammography mammography NOUN cana-572 59 9 is be AUX cana-572 59 10 the the DET cana-572 59 11 method method NOUN cana-572 59 12 that that PRON cana-572 59 13 is be AUX cana-572 59 14 most most ADV cana-572 59 15 widely widely ADV cana-572 59 16 employed employ VERB cana-572 59 17 . . PUNCT cana-572 60 1 as as ADP cana-572 60 2 an an DET cana-572 60 3 illustration illustration NOUN cana-572 60 4 , , PUNCT cana-572 60 5 it it PRON cana-572 60 6 is be AUX cana-572 60 7 advised advise VERB cana-572 60 8 that that SCONJ cana-572 60 9 women woman NOUN cana-572 60 10 who who PRON cana-572 60 11 are be AUX cana-572 60 12 forty forty NUM cana-572 60 13 years year NOUN cana-572 60 14 old old ADJ cana-572 60 15 or or CCONJ cana-572 60 16 older old ADJ cana-572 60 17 go go VERB cana-572 60 18 through through ADP cana-572 60 19 a a DET cana-572 60 20 mammographic mammographic ADJ cana-572 60 21 screening screening NOUN cana-572 61 1 [ [ X cana-572 61 2 3 3 NUM cana-572 61 3 , , PUNCT cana-572 61 4 4 4 NUM cana-572 61 5 ] ] PUNCT cana-572 61 6 . . PUNCT cana-572 62 1 the the DET cana-572 62 2 digital digital ADJ cana-572 62 3 mammogram mammogram NOUN cana-572 62 4 and and CCONJ cana-572 62 5 the the DET cana-572 62 6 digital digital ADJ cana-572 62 7 breast breast NOUN cana-572 62 8 tom tom PROPN cana-572 62 9 synthesis synthesis NOUN cana-572 62 10 ( ( PUNCT cana-572 62 11 dbt dbt PROPN cana-572 62 12 ) ) PUNCT cana-572 62 13 are be AUX cana-572 62 14 the the DET cana-572 62 15 two two NUM cana-572 62 16 instruments instrument NOUN cana-572 62 17 that that PRON cana-572 62 18 make make VERB cana-572 62 19 up up ADP cana-572 62 20 the the DET cana-572 62 21 majority majority NOUN cana-572 62 22 of of ADP cana-572 62 23 mammography mammography NOUN cana-572 62 24 . . PUNCT cana-572 63 1 however however ADV cana-572 63 2 , , PUNCT cana-572 63 3 it it PRON cana-572 63 4 has have AUX cana-572 63 5 been be AUX cana-572 63 6 shown show VERB cana-572 63 7 that that SCONJ cana-572 63 8 digital digital ADJ cana-572 63 9 mammography mammography NOUN cana-572 63 10 is be AUX cana-572 63 11 less less ADV cana-572 63 12 successful successful ADJ cana-572 63 13 in in ADP cana-572 63 14 individuals individual NOUN cana-572 63 15 who who PRON cana-572 63 16 have have VERB cana-572 63 17 thick thick ADJ cana-572 63 18 breasts breast NOUN cana-572 63 19 and and CCONJ cana-572 63 20 are be AUX cana-572 63 21 less less ADV cana-572 63 22 sensitive sensitive ADJ cana-572 63 23 to to ADP cana-572 63 24 tiny tiny ADJ cana-572 63 25 tumors tumor NOUN cana-572 63 26 ( ( PUNCT cana-572 63 27 tumors tumor NOUN cana-572 63 28 with with ADP cana-572 63 29 a a DET cana-572 63 30 volume volume NOUN cana-572 63 31 of of ADP cana-572 63 32 less less ADJ cana-572 63 33 than than ADP cana-572 63 34 1 1 NUM cana-572 63 35 mm mm NOUN cana-572 64 1 [ [ X cana-572 64 2 5 5 NUM cana-572 64 3 ] ] PUNCT cana-572 64 4 ) ) PUNCT cana-572 64 5 . . PUNCT cana-572 65 1 this this PRON cana-572 65 2 is be AUX cana-572 65 3 despite despite SCONJ cana-572 65 4 the the DET cana-572 65 5 fact fact NOUN cana-572 65 6 that that SCONJ cana-572 65 7 the the DET cana-572 65 8 digital digital ADJ cana-572 65 9 mammogram mammogram NOUN cana-572 65 10 is be AUX cana-572 65 11 the the DET cana-572 65 12 most most ADV cana-572 65 13 often often ADV cana-572 65 14 used use VERB cana-572 65 15 detection detection NOUN cana-572 65 16 method method NOUN cana-572 65 17 for for ADP cana-572 65 18 breast breast NOUN cana-572 65 19 cancer cancer NOUN cana-572 65 20 . . PUNCT cana-572 66 1 on on ADP cana-572 66 2 the the DET cana-572 66 3 other other ADJ cana-572 66 4 hand hand NOUN cana-572 66 5 , , PUNCT cana-572 66 6 these these DET cana-572 66 7 drawbacks drawback NOUN cana-572 66 8 are be AUX cana-572 66 9 circumvented circumvent VERB cana-572 66 10 by by ADP cana-572 66 11 dbtthe dbtthe NOUN cana-572 66 12 three three NUM cana-572 66 13 - - PUNCT cana-572 66 14 dimensional dimensional ADJ cana-572 66 15 mammogram mammogram NOUN cana-572 66 16 , , PUNCT cana-572 66 17 which which PRON cana-572 66 18 is be AUX cana-572 66 19 a a DET cana-572 66 20 more more ADV cana-572 66 21 advanced advanced ADJ cana-572 66 22 method method NOUN cana-572 66 23 of of ADP cana-572 66 24 mammography mammography NOUN cana-572 66 25 , , PUNCT cana-572 66 26 is be AUX cana-572 66 27 another another DET cana-572 66 28 name name NOUN cana-572 66 29 for for ADP cana-572 66 30 this this DET cana-572 66 31 examination examination NOUN cana-572 66 32 .. .. PUNCT cana-572 66 33 in in ADP cana-572 66 34 general general ADJ cana-572 66 35 , , PUNCT cana-572 66 36 it it PRON cana-572 66 37 offers offer VERB cana-572 66 38 a a DET cana-572 66 39 greater great ADJ cana-572 66 40 level level NOUN cana-572 66 41 of of ADP cana-572 66 42 diagnostic diagnostic ADJ cana-572 66 43 accuracy accuracy NOUN cana-572 66 44 compared compare VERB cana-572 66 45 to to ADP cana-572 66 46 the the DET cana-572 66 47 twodimensional twodimensional ADJ cana-572 66 48 mammogram mammogram NOUN cana-572 66 49 [ [ X cana-572 66 50 6 6 NUM cana-572 66 51 ] ] PUNCT cana-572 66 52 . . PUNCT cana-572 67 1 on on ADP cana-572 67 2 the the DET cana-572 67 3 other other ADJ cana-572 67 4 hand hand NOUN cana-572 67 5 , , PUNCT cana-572 67 6 when when SCONJ cana-572 67 7 these these DET cana-572 67 8 two two NUM cana-572 67 9 methods method NOUN cana-572 67 10 were be AUX cana-572 67 11 utilized utilize VERB cana-572 67 12 for for ADP cana-572 67 13 screening screen VERB cana-572 67 14 purposes purpose NOUN cana-572 67 15 , , PUNCT cana-572 67 16 there there PRON cana-572 67 17 was be VERB cana-572 67 18 not not PART cana-572 67 19 a a DET cana-572 67 20 discernible discernible ADJ cana-572 67 21 difference difference NOUN cana-572 67 22 between between ADP cana-572 67 23 them they PRON cana-572 67 24 [ [ X cana-572 67 25 7 7 NUM cana-572 67 26 ] ] PUNCT cana-572 67 27 . . PUNCT cana-572 68 1 there there PRON cana-572 68 2 are be VERB cana-572 68 3 hopes hope NOUN cana-572 68 4 that that SCONJ cana-572 68 5 machine machine NOUN cana-572 68 6 learning learning NOUN cana-572 68 7 will will AUX cana-572 68 8 lead lead VERB cana-572 68 9 to to ADP cana-572 68 10 better well ADJ cana-572 68 11 health health NOUN cana-572 68 12 care care NOUN cana-572 68 13 , , PUNCT cana-572 68 14 especially especially ADV cana-572 68 15 in in ADP cana-572 68 16 specialized specialized ADJ cana-572 68 17 medical medical ADJ cana-572 68 18 fields field NOUN cana-572 68 19 like like ADP cana-572 68 20 pathology pathology NOUN cana-572 68 21 , , PUNCT cana-572 68 22 ophthalmology ophthalmology NOUN cana-572 68 23 , , PUNCT cana-572 68 24 diagnostic diagnostic ADJ cana-572 68 25 imaging imaging NOUN cana-572 68 26 , , PUNCT cana-572 68 27 and and CCONJ cana-572 68 28 cardiology cardiology NOUN cana-572 69 1 [ [ X cana-572 69 2 8 8 NUM cana-572 69 3 ] ] PUNCT cana-572 69 4 . . PUNCT cana-572 70 1 the the DET cana-572 70 2 faster fast ADJ cana-572 70 3 use use NOUN cana-572 70 4 of of ADP cana-572 70 5 machine machine NOUN cana-572 70 6 learning learn VERB cana-572 70 7 in in ADP cana-572 70 8 many many ADJ cana-572 70 9 medical medical ADJ cana-572 70 10 areas area NOUN cana-572 70 11 will will AUX cana-572 70 12 be be AUX cana-572 70 13 caused cause VERB cana-572 70 14 by by ADP cana-572 70 15 a a DET cana-572 70 16 number number NOUN cana-572 70 17 of of ADP cana-572 70 18 things thing NOUN cana-572 70 19 , , PUNCT cana-572 70 20 such such ADJ cana-572 70 21 as as ADP cana-572 70 22 the the DET cana-572 70 23 easy easy ADJ cana-572 70 24 access access NOUN cana-572 70 25 to to ADP cana-572 70 26 large large ADJ cana-572 70 27 amounts amount NOUN cana-572 70 28 of of ADP cana-572 70 29 medical medical ADJ cana-572 70 30 data datum NOUN cana-572 70 31 and and CCONJ cana-572 70 32 the the DET cana-572 70 33 progress progress NOUN cana-572 70 34 of of ADP cana-572 70 35 computer computer NOUN cana-572 70 36 technology technology NOUN cana-572 70 37 . . PUNCT cana-572 71 1 however however ADV cana-572 71 2 , , PUNCT cana-572 71 3 even even ADV cana-572 71 4 with with ADP cana-572 71 5 these these DET cana-572 71 6 good good ADJ cana-572 71 7 gains gain NOUN cana-572 71 8 , , PUNCT cana-572 71 9 it it PRON cana-572 71 10 is be AUX cana-572 71 11 still still ADV cana-572 71 12 not not PART cana-572 71 13 clear clear ADJ cana-572 71 14 how how SCONJ cana-572 71 15 machine machine NOUN cana-572 71 16 learning learning NOUN cana-572 71 17 can can AUX cana-572 71 18 be be AUX cana-572 71 19 used use VERB cana-572 71 20 in in ADP cana-572 71 21 a a DET cana-572 71 22 communications communication NOUN cana-572 71 23 on on ADP cana-572 71 24 applied apply VERB cana-572 71 25 nonlinear nonlinear ADJ cana-572 71 26 analysis analysis NOUN cana-572 71 27 issn issn NOUN cana-572 71 28 : : PUNCT cana-572 71 29 1074 1074 NUM cana-572 71 30 - - PUNCT cana-572 71 31 133x 133x NUM cana-572 71 32 vol vol NOUN cana-572 71 33 31 31 NUM cana-572 71 34 no no NOUN cana-572 71 35 . . NOUN cana-572 71 36 2 2 NUM cana-572 71 37 ( ( PUNCT cana-572 71 38 2024 2024 NUM cana-572 71 39 ) ) PUNCT cana-572 71 40 336 336 NUM cana-572 72 1 https://internationalpubls.com https://internationalpubls.com X cana-572 73 1 therapeutic therapeutic ADJ cana-572 73 2 setting setting NOUN cana-572 73 3 [ [ X cana-572 73 4 9–11 9–11 X cana-572 73 5 ] ] PUNCT cana-572 73 6 . . PUNCT cana-572 74 1 people people NOUN cana-572 74 2 are be AUX cana-572 74 3 worried worried ADJ cana-572 74 4 about about ADP cana-572 74 5 their their PRON cana-572 74 6 privacy privacy NOUN cana-572 74 7 , , PUNCT cana-572 74 8 do do AUX cana-572 74 9 n't not PART cana-572 74 10 trust trust VERB cana-572 74 11 the the DET cana-572 74 12 technology technology NOUN cana-572 74 13 , , PUNCT cana-572 74 14 and and CCONJ cana-572 74 15 think think VERB cana-572 74 16 that that SCONJ cana-572 74 17 machine machine NOUN cana-572 74 18 learning learning NOUN cana-572 74 19 might might AUX cana-572 74 20 be be AUX cana-572 74 21 biased bias VERB cana-572 74 22 without without ADP cana-572 74 23 meaning mean VERB cana-572 74 24 to to PART cana-572 74 25 be be AUX cana-572 74 26 [ [ X cana-572 74 27 8 8 NUM cana-572 74 28 , , PUNCT cana-572 74 29 12–14 12–14 NUM cana-572 74 30 ] ] PUNCT cana-572 74 31 . . PUNCT cana-572 75 1 these these PRON cana-572 75 2 are be AUX cana-572 75 3 some some PRON cana-572 75 4 of of ADP cana-572 75 5 the the DET cana-572 75 6 problems problem NOUN cana-572 75 7 that that PRON cana-572 75 8 have have AUX cana-572 75 9 n't not PART cana-572 75 10 been be AUX cana-572 75 11 fully fully ADV cana-572 75 12 looked look VERB cana-572 75 13 into into ADP cana-572 75 14 yet yet ADV cana-572 75 15 . . PUNCT cana-572 76 1 researchers researcher NOUN cana-572 76 2 have have AUX cana-572 76 3 looked look VERB cana-572 76 4 into into ADP cana-572 76 5 how how SCONJ cana-572 76 6 machine machine NOUN cana-572 76 7 learning learning NOUN cana-572 76 8 can can AUX cana-572 76 9 be be AUX cana-572 76 10 used use VERB cana-572 76 11 in in ADP cana-572 76 12 the the DET cana-572 76 13 field field NOUN cana-572 76 14 of of ADP cana-572 76 15 breast breast NOUN cana-572 76 16 cancer cancer NOUN cana-572 76 17 for for ADP cana-572 76 18 a a DET cana-572 76 19 number number NOUN cana-572 76 20 of of ADP cana-572 76 21 reasons reason NOUN cana-572 76 22 , , PUNCT cana-572 76 23 such such ADJ cana-572 76 24 as as ADP cana-572 76 25 to to PART cana-572 76 26 predict predict VERB cana-572 76 27 and and CCONJ cana-572 76 28 screen screen VERB cana-572 76 29 for for ADP cana-572 76 30 the the DET cana-572 76 31 disease disease NOUN cana-572 76 32 [ [ X cana-572 76 33 15 15 NUM cana-572 76 34 ] ] PUNCT cana-572 76 35 , , PUNCT cana-572 76 36 to to PART cana-572 76 37 predict predict VERB cana-572 76 38 when when SCONJ cana-572 76 39 cancer cancer NOUN cana-572 76 40 will will AUX cana-572 76 41 come come VERB cana-572 76 42 back back ADV cana-572 77 1 [ [ X cana-572 77 2 16 16 NUM cana-572 77 3 ] ] PUNCT cana-572 77 4 , , PUNCT cana-572 77 5 to to PART cana-572 77 6 predict predict VERB cana-572 77 7 how how SCONJ cana-572 77 8 long long ADJ cana-572 77 9 a a DET cana-572 77 10 patient patient NOUN cana-572 77 11 will will AUX cana-572 77 12 live live VERB cana-572 77 13 [ [ X cana-572 77 14 17 17 NUM cana-572 77 15 ] ] PUNCT cana-572 77 16 , , PUNCT cana-572 77 17 to to PART cana-572 77 18 predict predict VERB cana-572 77 19 breast breast NOUN cana-572 77 20 density density NOUN cana-572 77 21 [ [ X cana-572 77 22 18 18 NUM cana-572 77 23 ] ] PUNCT cana-572 77 24 , , PUNCT cana-572 77 25 and and CCONJ cana-572 77 26 to to PART cana-572 77 27 help help VERB cana-572 77 28 with with ADP cana-572 77 29 treatments treatment NOUN cana-572 77 30 and and CCONJ cana-572 77 31 management management NOUN cana-572 77 32 of of ADP cana-572 77 33 the the DET cana-572 77 34 disease disease NOUN cana-572 77 35 [ [ X cana-572 77 36 19 19 NUM cana-572 77 37 ] ] PUNCT cana-572 77 38 . . PUNCT cana-572 78 1 researchers researcher NOUN cana-572 78 2 have have AUX cana-572 78 3 looked look VERB cana-572 78 4 into into ADP cana-572 78 5 a a DET cana-572 78 6 number number NOUN cana-572 78 7 of of ADP cana-572 78 8 different different ADJ cana-572 78 9 data datum NOUN cana-572 78 10 sources source NOUN cana-572 78 11 and and CCONJ cana-572 78 12 machine machine NOUN cana-572 78 13 learning learning NOUN cana-572 78 14 methods method NOUN cana-572 78 15 to to PART cana-572 78 16 see see VERB cana-572 78 17 how how SCONJ cana-572 78 18 they they PRON cana-572 78 19 might might AUX cana-572 78 20 be be AUX cana-572 78 21 useful useful ADJ cana-572 78 22 in in ADP cana-572 78 23 different different ADJ cana-572 78 24 breast breast NOUN cana-572 78 25 cancer cancer NOUN cana-572 78 26 clinical clinical ADJ cana-572 78 27 situations situation NOUN cana-572 78 28 . . PUNCT cana-572 79 1 these these DET cana-572 79 2 data datum NOUN cana-572 79 3 sources source NOUN cana-572 79 4 include include VERB cana-572 79 5 sociodemographic sociodemographic ADJ cana-572 79 6 and and CCONJ cana-572 79 7 clinical clinical ADJ cana-572 79 8 data datum NOUN cana-572 79 9 , , PUNCT cana-572 79 10 genetic genetic ADJ cana-572 79 11 data datum NOUN cana-572 79 12 , , PUNCT cana-572 79 13 imaging imaging NOUN cana-572 79 14 data datum NOUN cana-572 79 15 , , PUNCT cana-572 79 16 and and CCONJ cana-572 79 17 more more ADJ cana-572 79 18 . . PUNCT cana-572 80 1 it it PRON cana-572 80 2 can can AUX cana-572 80 3 basically basically ADV cana-572 80 4 divide divide VERB cana-572 80 5 the the DET cana-572 80 6 use use NOUN cana-572 80 7 of of ADP cana-572 80 8 machine machine NOUN cana-572 80 9 learning learning NOUN cana-572 80 10 in in ADP cana-572 80 11 this this DET cana-572 80 12 field field NOUN cana-572 80 13 of of ADP cana-572 80 14 study study NOUN cana-572 80 15 into into ADP cana-572 80 16 three three NUM cana-572 80 17 main main ADJ cana-572 80 18 groups group NOUN cana-572 80 19 : : PUNCT cana-572 80 20 as as ADP cana-572 80 21 a a DET cana-572 80 22 screening screening NOUN cana-572 80 23 tool tool NOUN cana-572 80 24 , , PUNCT cana-572 80 25 a a DET cana-572 80 26 diagnostic diagnostic ADJ cana-572 80 27 tool tool NOUN cana-572 80 28 , , PUNCT cana-572 80 29 or or CCONJ cana-572 80 30 a a DET cana-572 80 31 prediction prediction NOUN cana-572 80 32 tool tool NOUN cana-572 80 33 . . PUNCT cana-572 81 1 it it PRON cana-572 81 2 's be AUX cana-572 81 3 just just ADV cana-572 81 4 that that SCONJ cana-572 81 5 most most ADJ cana-572 81 6 studies study NOUN cana-572 81 7 do do AUX cana-572 81 8 n't not PART cana-572 81 9 make make VERB cana-572 81 10 it it PRON cana-572 81 11 clear clear ADJ cana-572 81 12 what what DET cana-572 81 13 role role NOUN cana-572 81 14 their their PRON cana-572 81 15 machine machine NOUN cana-572 81 16 learning learn VERB cana-572 81 17 model model NOUN cana-572 81 18 plays play VERB cana-572 81 19 in in ADP cana-572 81 20 the the DET cana-572 81 21 clinical clinical ADJ cana-572 81 22 setting setting NOUN cana-572 81 23 or or CCONJ cana-572 81 24 how how SCONJ cana-572 81 25 it it PRON cana-572 81 26 can can AUX cana-572 81 27 be be AUX cana-572 81 28 used use VERB cana-572 81 29 in in ADP cana-572 81 30 real real ADJ cana-572 81 31 life life NOUN cana-572 81 32 . . PUNCT cana-572 82 1 the the DET cana-572 82 2 reason reason NOUN cana-572 82 3 for for ADP cana-572 82 4 this this PRON cana-572 82 5 is be AUX cana-572 82 6 that that SCONJ cana-572 82 7 these these DET cana-572 82 8 different different ADJ cana-572 82 9 tasks task NOUN cana-572 82 10 of of ADP cana-572 82 11 machine machine NOUN cana-572 82 12 learning learning NOUN cana-572 82 13 will will AUX cana-572 82 14 have have VERB cana-572 82 15 an an DET cana-572 82 16 impact impact NOUN cana-572 82 17 on on ADP cana-572 82 18 how how SCONJ cana-572 82 19 the the DET cana-572 82 20 model model NOUN cana-572 82 21 is be AUX cana-572 82 22 built build VERB cana-572 82 23 and and CCONJ cana-572 82 24 used.meena used.meena NUM cana-572 82 25 et et NOUN cana-572 82 26 al al PROPN cana-572 82 27 . . PROPN cana-572 83 1 ( ( PUNCT cana-572 83 2 2023 2023 NUM cana-572 83 3 ) ) PUNCT cana-572 84 1 [ [ X cana-572 84 2 20 20 NUM cana-572 84 3 ] ] PUNCT cana-572 84 4 planned plan VERB cana-572 84 5 a a DET cana-572 84 6 breast breast NOUN cana-572 84 7 cancer cancer NOUN cana-572 84 8 uncovering uncover VERB cana-572 84 9 model model NOUN cana-572 84 10 using use VERB cana-572 84 11 the the DET cana-572 84 12 curvelet curvelet NOUN cana-572 84 13 transform transform NOUN cana-572 84 14 for for ADP cana-572 84 15 feature feature NOUN cana-572 84 16 extraction extraction NOUN cana-572 84 17 , , PUNCT cana-572 84 18 adaptive adaptive ADJ cana-572 84 19 particle particle NOUN cana-572 84 20 swarm swarm NOUN cana-572 84 21 optimization optimization NOUN cana-572 84 22 for for ADP cana-572 84 23 feature feature NOUN cana-572 84 24 selection selection NOUN cana-572 84 25 , , PUNCT cana-572 84 26 and and CCONJ cana-572 84 27 support support VERB cana-572 84 28 vector vector NOUN cana-572 84 29 machines machine NOUN cana-572 84 30 for for ADP cana-572 84 31 classification classification NOUN cana-572 84 32 , , PUNCT cana-572 84 33 achieving achieve VERB cana-572 84 34 higher high ADJ cana-572 84 35 accuracy accuracy NOUN cana-572 84 36 rates rate NOUN cana-572 84 37 compared compare VERB cana-572 84 38 to to ADP cana-572 84 39 previous previous ADJ cana-572 84 40 approaches approach NOUN cana-572 84 41 . . PUNCT cana-572 85 1 nurhayati nurhayati PROPN cana-572 85 2 et et PROPN cana-572 85 3 al al PROPN cana-572 85 4 . . PROPN cana-572 85 5 ( ( PUNCT cana-572 85 6 2020 2020 NUM cana-572 85 7 ) ) PUNCT cana-572 86 1 [ [ X cana-572 86 2 21 21 NUM cana-572 86 3 ] ] X cana-572 86 4 utilized utilize VERB cana-572 86 5 pso pso NOUN cana-572 86 6 for for ADP cana-572 86 7 feature feature NOUN cana-572 86 8 selection selection NOUN cana-572 86 9 in in ADP cana-572 86 10 various various ADJ cana-572 86 11 classification classification NOUN cana-572 86 12 algorithms algorithm NOUN cana-572 86 13 to to PART cana-572 86 14 improve improve VERB cana-572 86 15 breast breast NOUN cana-572 86 16 cancer cancer NOUN cana-572 86 17 diagnosis diagnosis NOUN cana-572 86 18 , , PUNCT cana-572 86 19 highlighting highlight VERB cana-572 86 20 its its PRON cana-572 86 21 effectiveness effectiveness NOUN cana-572 86 22 but but CCONJ cana-572 86 23 noting note VERB cana-572 86 24 that that SCONJ cana-572 86 25 it it PRON cana-572 86 26 could could AUX cana-572 86 27 n't not PART cana-572 86 28 surpass surpass VERB cana-572 86 29 the the DET cana-572 86 30 performance performance NOUN cana-572 86 31 of of ADP cana-572 86 32 genetic genetic ADJ cana-572 86 33 algorithms algorithm NOUN cana-572 86 34 . . PUNCT cana-572 87 1 sannasi sannasi NOUN cana-572 87 2 chakravarthy chakravarthy ADJ cana-572 87 3 et et PROPN cana-572 87 4 al al PROPN cana-572 87 5 . . PROPN cana-572 88 1 ( ( PUNCT cana-572 88 2 2022 2022 NUM cana-572 88 3 ) ) PUNCT cana-572 89 1 [ [ X cana-572 89 2 22 22 NUM cana-572 89 3 ] ] PUNCT cana-572 89 4 designed design VERB cana-572 89 5 a a DET cana-572 89 6 computer computer NOUN cana-572 89 7 - - PUNCT cana-572 89 8 aided aid VERB cana-572 89 9 diagnosis diagnosis NOUN cana-572 89 10 ( ( PUNCT cana-572 89 11 cad cad NOUN cana-572 89 12 ) ) PUNCT cana-572 89 13 system system NOUN cana-572 89 14 for for ADP cana-572 89 15 breast breast NOUN cana-572 89 16 cancer cancer NOUN cana-572 89 17 diagnosis diagnosis NOUN cana-572 89 18 using use VERB cana-572 89 19 the the DET cana-572 89 20 ebola ebola NOUN cana-572 89 21 optimization optimization NOUN cana-572 89 22 algorithm algorithm NOUN cana-572 89 23 ( ( PUNCT cana-572 89 24 eoa eoa PROPN cana-572 89 25 ) ) PUNCT cana-572 89 26 for for ADP cana-572 89 27 feature feature NOUN cana-572 89 28 selection selection NOUN cana-572 89 29 and and CCONJ cana-572 89 30 achieved achieve VERB cana-572 89 31 a a DET cana-572 89 32 maximum maximum ADJ cana-572 89 33 accuracy accuracy NOUN cana-572 89 34 of of ADP cana-572 89 35 97.19 97.19 NUM cana-572 89 36 % % NOUN cana-572 89 37 with with ADP cana-572 89 38 mk mk PROPN cana-572 89 39 . . PUNCT cana-572 90 1 svm svm PROPN cana-572 90 2 harish harish PROPN cana-572 90 3 et et PROPN cana-572 90 4 al al PROPN cana-572 90 5 . . PROPN cana-572 91 1 ( ( PUNCT cana-572 91 2 2022 2022 NUM cana-572 91 3 ) ) PUNCT cana-572 92 1 [ [ X cana-572 92 2 23 23 NUM cana-572 92 3 ] ] PUNCT cana-572 92 4 they they PRON cana-572 92 5 used use VERB cana-572 92 6 medical medical ADJ cana-572 92 7 image image NOUN cana-572 92 8 processing processing NOUN cana-572 92 9 methods method NOUN cana-572 92 10 like like ADP cana-572 92 11 convolutional convolutional ADJ cana-572 92 12 neural neural ADJ cana-572 92 13 networks network NOUN cana-572 92 14 ( ( PUNCT cana-572 92 15 cnn cnn PROPN cana-572 92 16 ) ) PUNCT cana-572 92 17 , , PUNCT cana-572 92 18 particle particle NOUN cana-572 92 19 swarm swarm NOUN cana-572 92 20 optimization optimization NOUN cana-572 92 21 ( ( PUNCT cana-572 92 22 pso pso NOUN cana-572 92 23 ) ) PUNCT cana-572 92 24 , , PUNCT cana-572 92 25 and and CCONJ cana-572 92 26 support support VERB cana-572 92 27 vector vector NOUN cana-572 92 28 machines machine NOUN cana-572 92 29 ( ( PUNCT cana-572 92 30 svm svm PROPN cana-572 92 31 ) ) PUNCT cana-572 92 32 to to PART cana-572 92 33 find find VERB cana-572 92 34 breast breast NOUN cana-572 92 35 cancer cancer NOUN cana-572 92 36 . . PUNCT cana-572 93 1 in in ADP cana-572 93 2 2023 2023 NUM cana-572 93 3 , , PUNCT cana-572 93 4 momtahen momtahen NOUN cana-572 93 5 et et PROPN cana-572 93 6 al al PROPN cana-572 93 7 . . PUNCT cana-572 94 1 [ [ X cana-572 94 2 24 24 NUM cana-572 94 3 ] ] PUNCT cana-572 94 4 suggested suggest VERB cana-572 94 5 a a DET cana-572 94 6 dob dob PROPN cana-572 94 7 - - PUNCT cana-572 94 8 scan scan ADJ cana-572 94 9 probe probe NOUN cana-572 94 10 that that PRON cana-572 94 11 uses use VERB cana-572 94 12 ensemble ensemble ADJ cana-572 94 13 learning learning NOUN cana-572 94 14 to to PART cana-572 94 15 find find VERB cana-572 94 16 breast breast NOUN cana-572 94 17 cancer cancer NOUN cana-572 94 18 earlier early ADV cana-572 94 19 and and CCONJ cana-572 94 20 achieve achieve VERB cana-572 94 21 high high ADJ cana-572 94 22 success success NOUN cana-572 94 23 rates rate NOUN cana-572 94 24 with with ADP cana-572 94 25 different different ADJ cana-572 94 26 regression regression NOUN cana-572 94 27 algorithms algorithm NOUN cana-572 94 28 . . PUNCT cana-572 95 1 in in ADP cana-572 95 2 2020 2020 NUM cana-572 95 3 , , PUNCT cana-572 95 4 baskaran baskaran ADV cana-572 95 5 et et PROPN cana-572 95 6 al al PROPN cana-572 95 7 . . PUNCT cana-572 96 1 [ [ X cana-572 96 2 25 25 NUM cana-572 96 3 ] ] PUNCT cana-572 96 4 looked look VERB cana-572 96 5 at at ADP cana-572 96 6 ga ga PROPN cana-572 96 7 and and CCONJ cana-572 96 8 pso pso NOUN cana-572 96 9 for for ADP cana-572 96 10 planning plan VERB cana-572 96 11 thermal thermal ADJ cana-572 96 12 treatment treatment NOUN cana-572 96 13 for for ADP cana-572 96 14 breast breast NOUN cana-572 96 15 cancer cancer NOUN cana-572 96 16 and and CCONJ cana-572 96 17 found find VERB cana-572 96 18 that that SCONJ cana-572 96 19 ga ga PROPN cana-572 96 20 did do VERB cana-572 96 21 better well ADV cana-572 96 22 for for ADP cana-572 96 23 global global ADJ cana-572 96 24 optimization optimization NOUN cana-572 96 25 than than ADP cana-572 96 26 pso pso NOUN cana-572 96 27 . . PUNCT cana-572 97 1 mani mani PROPN cana-572 97 2 et et PROPN cana-572 97 3 al al PROPN cana-572 97 4 . . PROPN cana-572 98 1 ( ( PUNCT cana-572 98 2 2020 2020 NUM cana-572 98 3 ) ) PUNCT cana-572 99 1 [ [ X cana-572 99 2 26 26 NUM cana-572 99 3 ] ] PUNCT cana-572 99 4 used use VERB cana-572 99 5 a a DET cana-572 99 6 decision decision NOUN cana-572 99 7 tree tree NOUN cana-572 99 8 classifier classifier NOUN cana-572 99 9 on on ADP cana-572 99 10 gene gene NOUN cana-572 99 11 expression expression NOUN cana-572 99 12 data datum NOUN cana-572 99 13 for for ADP cana-572 99 14 breast breast NOUN cana-572 99 15 cancer cancer NOUN cana-572 99 16 diagnosis diagnosis NOUN cana-572 99 17 , , PUNCT cana-572 99 18 enhancing enhance VERB cana-572 99 19 results result NOUN cana-572 99 20 with with ADP cana-572 99 21 elephant elephant NOUN cana-572 99 22 herding herd VERB cana-572 99 23 optimization optimization NOUN cana-572 99 24 for for ADP cana-572 99 25 feature feature NOUN cana-572 99 26 transformation transformation NOUN cana-572 99 27 . . PUNCT cana-572 100 1 vilohit vilohit PROPN cana-572 100 2 et et PROPN cana-572 100 3 al al PROPN cana-572 100 4 . . PROPN cana-572 101 1 ( ( PUNCT cana-572 101 2 2022 2022 NUM cana-572 101 3 ) ) PUNCT cana-572 102 1 [ [ X cana-572 102 2 27 27 NUM cana-572 102 3 ] ] PUNCT cana-572 102 4 implemented implement VERB cana-572 102 5 a a DET cana-572 102 6 decision decision NOUN cana-572 102 7 tree tree NOUN cana-572 102 8 classifier classifier NOUN cana-572 102 9 on on ADP cana-572 102 10 gene gene NOUN cana-572 102 11 expression expression NOUN cana-572 102 12 data datum NOUN cana-572 102 13 , , PUNCT cana-572 102 14 enhancing enhance VERB cana-572 102 15 performance performance NOUN cana-572 102 16 with with ADP cana-572 102 17 elephant elephant NOUN cana-572 102 18 herding herd VERB cana-572 102 19 optimization optimization NOUN cana-572 102 20 for for ADP cana-572 102 21 feature feature NOUN cana-572 102 22 transformation transformation NOUN cana-572 102 23 and and CCONJ cana-572 102 24 principal principal ADJ cana-572 102 25 component component NOUN cana-572 102 26 analysis analysis NOUN cana-572 102 27 for for ADP cana-572 102 28 dimensionality dimensionality NOUN cana-572 102 29 reduction reduction NOUN cana-572 102 30 . . PUNCT cana-572 103 1 mitra mitra PROPN cana-572 103 2 et et PROPN cana-572 103 3 al al PROPN cana-572 103 4 . . PROPN cana-572 103 5 ( ( PUNCT cana-572 103 6 2023 2023 NUM cana-572 103 7 ) ) PUNCT cana-572 104 1 [ [ X cana-572 104 2 28 28 NUM cana-572 104 3 ] ] PUNCT cana-572 104 4 applied apply VERB cana-572 104 5 particle particle NOUN cana-572 104 6 swarm swarm NOUN cana-572 104 7 optimization optimization NOUN cana-572 104 8 to to PART cana-572 104 9 identify identify VERB cana-572 104 10 disease disease NOUN cana-572 104 11 - - PUNCT cana-572 104 12 causing cause VERB cana-572 104 13 genes gene NOUN cana-572 104 14 and and CCONJ cana-572 104 15 developed develop VERB cana-572 104 16 hybrid hybrid ADJ cana-572 104 17 algorithms algorithm NOUN cana-572 104 18 for for ADP cana-572 104 19 the the DET cana-572 104 20 classification classification NOUN cana-572 104 21 of of ADP cana-572 104 22 triple triple ADJ cana-572 104 23 negative negative ADJ cana-572 104 24 breast breast NOUN cana-572 104 25 cancer cancer NOUN cana-572 104 26 , , PUNCT cana-572 104 27 achieving achieve VERB cana-572 104 28 high high ADJ cana-572 104 29 accuracy accuracy NOUN cana-572 104 30 rates rate NOUN cana-572 104 31 . . PUNCT cana-572 105 1 many many ADJ cana-572 105 2 years year NOUN cana-572 105 3 ago ago ADV cana-572 105 4 , , PUNCT cana-572 105 5 aouragh aouragh NOUN cana-572 105 6 et et PROPN cana-572 105 7 al al PROPN cana-572 105 8 . . PUNCT cana-572 106 1 [ [ X cana-572 106 2 29 29 NUM cana-572 106 3 ] ] PUNCT cana-572 106 4 looked look VERB cana-572 106 5 at at ADP cana-572 106 6 different different ADJ cana-572 106 7 machine machine NOUN cana-572 106 8 learning learning NOUN cana-572 106 9 methods method NOUN cana-572 106 10 for for ADP cana-572 106 11 classifying classify VERB cana-572 106 12 breast breast NOUN cana-572 106 13 cancer cancer NOUN cana-572 106 14 and and CCONJ cana-572 106 15 improved improve VERB cana-572 106 16 them they PRON cana-572 106 17 by by ADP cana-572 106 18 balancing balance VERB cana-572 106 19 the the DET cana-572 106 20 data datum NOUN cana-572 106 21 , , PUNCT cana-572 106 22 choosing choose VERB cana-572 106 23 the the DET cana-572 106 24 right right ADJ cana-572 106 25 features feature NOUN cana-572 106 26 , , PUNCT cana-572 106 27 and and CCONJ cana-572 106 28 optimizing optimize VERB cana-572 106 29 hyperparameters hyperparameter NOUN cana-572 106 30 . . PUNCT cana-572 107 1 the the DET cana-572 107 2 results result NOUN cana-572 107 3 were be AUX cana-572 107 4 impressive impressive ADJ cana-572 107 5 , , PUNCT cana-572 107 6 with with ADP cana-572 107 7 over over ADP cana-572 107 8 98 98 NUM cana-572 107 9 % % NOUN cana-572 107 10 accuracy accuracy NOUN cana-572 107 11 across across ADP cana-572 107 12 all all DET cana-572 107 13 measures measure NOUN cana-572 107 14 . . PUNCT cana-572 108 1 3 3 X cana-572 108 2 . . X cana-572 108 3 materials material NOUN cana-572 108 4 and and CCONJ cana-572 108 5 methods method NOUN cana-572 108 6 the the DET cana-572 108 7 following follow VERB cana-572 108 8 subsections subsection NOUN cana-572 108 9 briefly briefly ADV cana-572 108 10 summarize summarize VERB cana-572 108 11 this this DET cana-572 108 12 paper paper NOUN cana-572 108 13 's 's PART cana-572 108 14 research research NOUN cana-572 108 15 materials material NOUN cana-572 108 16 and and CCONJ cana-572 108 17 methods method NOUN cana-572 108 18 . . PUNCT cana-572 109 1 communications communication NOUN cana-572 109 2 on on ADP cana-572 109 3 applied apply VERB cana-572 109 4 nonlinear nonlinear ADJ cana-572 109 5 analysis analysis NOUN cana-572 109 6 issn issn NOUN cana-572 109 7 : : PUNCT cana-572 109 8 1074 1074 NUM cana-572 109 9 - - PUNCT cana-572 109 10 133x 133x NUM cana-572 109 11 vol vol NOUN cana-572 109 12 31 31 NUM cana-572 109 13 no no NOUN cana-572 109 14 . . NOUN cana-572 109 15 2 2 NUM cana-572 109 16 ( ( PUNCT cana-572 109 17 2024 2024 NUM cana-572 109 18 ) ) PUNCT cana-572 109 19 337 337 NUM cana-572 109 20 https://internationalpubls.com https://internationalpubls.com X cana-572 109 21 dataset dataset NOUN cana-572 109 22 and and CCONJ cana-572 109 23 tools tool NOUN cana-572 109 24 breast breast NOUN cana-572 109 25 cancer cancer NOUN cana-572 109 26 wisconsin wisconsin PROPN cana-572 109 27 ( ( PUNCT cana-572 109 28 diagnostic diagnostic ADJ cana-572 109 29 ) ) PUNCT cana-572 109 30 data datum NOUN cana-572 109 31 set set VERB cana-572 109 32 from from ADP cana-572 109 33 uci uci PROPN cana-572 109 34 machine machine NOUN cana-572 109 35 learning learn VERB cana-572 109 36 repository repository NOUN cana-572 109 37 is be AUX cana-572 109 38 being be AUX cana-572 109 39 tested test VERB cana-572 109 40 [ [ PUNCT cana-572 109 41 28 28 NUM cana-572 109 42 ] ] PUNCT cana-572 109 43 . . PUNCT cana-572 110 1 wisconsin wisconsin PROPN cana-572 110 2 breast breast PROPN cana-572 110 3 cancer cancer NOUN cana-572 110 4 diagnosis diagnosis NOUN cana-572 110 5 from from ADP cana-572 110 6 uci uci PROPN cana-572 110 7 repository repository NOUN cana-572 110 8 having have VERB cana-572 110 9 569 569 NUM cana-572 110 10 samples sample NOUN cana-572 110 11 357 357 NUM cana-572 110 12 benign benign ADJ cana-572 110 13 and and CCONJ cana-572 110 14 212 212 NUM cana-572 110 15 malignant malignant ADJ cana-572 110 16 .. .. PUNCT cana-572 110 17 methodology methodology NOUN cana-572 110 18 for for ADP cana-572 110 19 the the DET cana-572 110 20 proposed propose VERB cana-572 110 21 system system NOUN cana-572 110 22 the the DET cana-572 110 23 suggested suggested ADJ cana-572 110 24 approach approach NOUN cana-572 110 25 distinguishes distinguish VERB cana-572 110 26 malignant malignant ADJ cana-572 110 27 from from ADP cana-572 110 28 benign benign ADJ cana-572 110 29 cells cell NOUN cana-572 110 30 . . PUNCT cana-572 111 1 we we PRON cana-572 111 2 improved improve VERB cana-572 111 3 breast breast NOUN cana-572 111 4 cancer cancer NOUN cana-572 111 5 diagnosis diagnosis NOUN cana-572 111 6 machine machine NOUN cana-572 111 7 learning learn VERB cana-572 111 8 classification classification NOUN cana-572 111 9 models model NOUN cana-572 111 10 in in ADP cana-572 111 11 our our PRON cana-572 111 12 research research NOUN cana-572 111 13 . . PUNCT cana-572 112 1 to to PART cana-572 112 2 compare compare VERB cana-572 112 3 classifier classifier NOUN cana-572 112 4 accuracy accuracy NOUN cana-572 112 5 , , PUNCT cana-572 112 6 all all DET cana-572 112 7 characteristics characteristic NOUN cana-572 112 8 and and CCONJ cana-572 112 9 chosen choose VERB cana-572 112 10 features feature NOUN cana-572 112 11 were be AUX cana-572 112 12 examined examine VERB cana-572 112 13 independently independently ADV cana-572 112 14 . . PUNCT cana-572 113 1 we we PRON cana-572 113 2 employed employ VERB cana-572 113 3 wrapper wrapper NOUN cana-572 113 4 - - PUNCT cana-572 113 5 based base VERB cana-572 113 6 feature feature NOUN cana-572 113 7 selection selection NOUN cana-572 113 8 , , PUNCT cana-572 113 9 nature nature NOUN cana-572 113 10 - - PUNCT cana-572 113 11 inspired inspire VERB cana-572 113 12 algorithms algorithm NOUN cana-572 113 13 like like ADP cana-572 113 14 ( ( PUNCT cana-572 113 15 pso pso NOUN cana-572 113 16 ) ) PUNCT cana-572 113 17 , , PUNCT cana-572 113 18 and and CCONJ cana-572 113 19 a a DET cana-572 113 20 hybrid hybrid NOUN cana-572 113 21 of of ADP cana-572 113 22 pso pso NOUN cana-572 113 23 and and CCONJ cana-572 113 24 grey grey ADJ cana-572 113 25 wolf wolf PROPN cana-572 113 26 optimizer optimizer NOUN cana-572 113 27 to to PART cana-572 113 28 discover discover VERB cana-572 113 29 key key ADJ cana-572 113 30 features feature NOUN cana-572 113 31 . . PUNCT cana-572 114 1 popular popular ADJ cana-572 114 2 machine machine NOUN cana-572 114 3 learning learn VERB cana-572 114 4 classifiers classifier NOUN cana-572 114 5 svm svm PROPN cana-572 114 6 , , PUNCT cana-572 114 7 knn knn PROPN cana-572 114 8 , , PUNCT cana-572 114 9 lr lr INTJ cana-572 114 10 , , PUNCT cana-572 114 11 and and CCONJ cana-572 114 12 rf rf NOUN cana-572 114 13 were be AUX cana-572 114 14 employed employ VERB cana-572 114 15 on on ADP cana-572 114 16 these these DET cana-572 114 17 features feature NOUN cana-572 114 18 . . PUNCT cana-572 115 1 the the DET cana-572 115 2 suggested suggest VERB cana-572 115 3 system system NOUN cana-572 115 4 has have VERB cana-572 115 5 five five NUM cana-572 115 6 stages stage NOUN cana-572 115 7 : : PUNCT cana-572 115 8 ( ( PUNCT cana-572 115 9 1 1 X cana-572 115 10 ) ) PUNCT cana-572 115 11 pre pre ADJ cana-572 115 12 - - ADJ cana-572 115 13 processing processing NOUN cana-572 115 14 of of ADP cana-572 115 15 the the DET cana-572 115 16 data datum NOUN cana-572 115 17 , , PUNCT cana-572 115 18 ( ( PUNCT cana-572 115 19 2 2 X cana-572 115 20 ) ) PUNCT cana-572 115 21 data datum NOUN cana-572 115 22 imbalance imbalance NOUN cana-572 115 23 management management NOUN cana-572 115 24 , , PUNCT cana-572 115 25 ( ( PUNCT cana-572 115 26 3 3 X cana-572 115 27 ) ) PUNCT cana-572 115 28 feature feature NOUN cana-572 115 29 selection selection NOUN cana-572 115 30 , , PUNCT cana-572 115 31 ( ( PUNCT cana-572 115 32 4 4 X cana-572 115 33 ) ) PUNCT cana-572 115 34 classes class NOUN cana-572 115 35 derived derive VERB cana-572 115 36 by by ADP cana-572 115 37 machine machine NOUN cana-572 115 38 learning learning NOUN cana-572 115 39 , , PUNCT cana-572 115 40 as as ADV cana-572 115 41 well well ADV cana-572 115 42 as as ADP cana-572 115 43 ( ( PUNCT cana-572 115 44 5 5 NUM cana-572 115 45 ) ) PUNCT cana-572 115 46 the the DET cana-572 115 47 evaluation evaluation NOUN cana-572 115 48 of of ADP cana-572 115 49 the the DET cana-572 115 50 performance performance NOUN cana-572 115 51 of of ADP cana-572 115 52 the the DET cana-572 115 53 classifier classifier NOUN cana-572 115 54 . . PUNCT cana-572 116 1 data datum NOUN cana-572 116 2 pre pre ADJ cana-572 116 3 - - ADJ cana-572 116 4 processing processing ADJ cana-572 116 5 and and CCONJ cana-572 116 6 cross cross VERB cana-572 116 7 validation validation NOUN cana-572 116 8 preprocessing preprocessing NOUN cana-572 116 9 data datum NOUN cana-572 116 10 is be AUX cana-572 116 11 a a DET cana-572 116 12 necessary necessary ADJ cana-572 116 13 step step NOUN cana-572 116 14 in in ADP cana-572 116 15 order order NOUN cana-572 116 16 to to PART cana-572 116 17 represent represent VERB cana-572 116 18 data datum NOUN cana-572 116 19 efficiently efficiently ADV cana-572 116 20 . . PUNCT cana-572 117 1 this this DET cana-572 117 2 phase phase NOUN cana-572 117 3 encompasses encompass VERB cana-572 117 4 the the DET cana-572 117 5 elimination elimination NOUN cana-572 117 6 of of ADP cana-572 117 7 absent absent ADJ cana-572 117 8 values value NOUN cana-572 117 9 and and CCONJ cana-572 117 10 the the DET cana-572 117 11 discretization discretization NOUN cana-572 117 12 of of ADP cana-572 117 13 features feature NOUN cana-572 117 14 , , PUNCT cana-572 117 15 which which PRON cana-572 117 16 involves involve VERB cana-572 117 17 converting convert VERB cana-572 117 18 numeric numeric ADJ cana-572 117 19 data datum NOUN cana-572 117 20 to to ADP cana-572 117 21 nominal nominal ADJ cana-572 117 22 . . PUNCT cana-572 118 1 discreteization discreteization NOUN cana-572 118 2 facilitates facilitate VERB cana-572 118 3 the the DET cana-572 118 4 generation generation NOUN cana-572 118 5 of of ADP cana-572 118 6 comprehensible comprehensible ADJ cana-572 118 7 branches branch NOUN cana-572 118 8 for for ADP cana-572 118 9 the the DET cana-572 118 10 decision decision NOUN cana-572 118 11 tree tree NOUN cana-572 118 12 , , PUNCT cana-572 118 13 as as SCONJ cana-572 118 14 opposed oppose VERB cana-572 118 15 to to ADP cana-572 118 16 branches branch NOUN cana-572 118 17 that that PRON cana-572 118 18 rely rely VERB cana-572 118 19 on on ADP cana-572 118 20 numerical numerical ADJ cana-572 118 21 values value NOUN cana-572 118 22 . . PUNCT cana-572 119 1 the the DET cana-572 119 2 feature feature NOUN cana-572 119 3 row row NOUN cana-572 119 4 containing contain VERB cana-572 119 5 missing miss VERB cana-572 119 6 values value NOUN cana-572 119 7 is be AUX cana-572 119 8 eliminated eliminate VERB cana-572 119 9 from from ADP cana-572 119 10 the the DET cana-572 119 11 dataset dataset NOUN cana-572 119 12 . . PUNCT cana-572 120 1 crossvalidation crossvalidation NOUN cana-572 120 2 is be AUX cana-572 120 3 a a DET cana-572 120 4 method method NOUN cana-572 120 5 employed employ VERB cana-572 120 6 to to PART cana-572 120 7 evaluate evaluate VERB cana-572 120 8 the the DET cana-572 120 9 efficiency efficiency NOUN cana-572 120 10 of of ADP cana-572 120 11 a a DET cana-572 120 12 machine machine NOUN cana-572 120 13 learning learning NOUN cana-572 120 14 model model NOUN cana-572 120 15 and and CCONJ cana-572 120 16 to to PART cana-572 120 17 alleviate alleviate VERB cana-572 120 18 concerns concern NOUN cana-572 120 19 , , PUNCT cana-572 120 20 including include VERB cana-572 120 21 overfitting overfitte VERB cana-572 120 22 . . PUNCT cana-572 121 1 the the DET cana-572 121 2 procedure procedure NOUN cana-572 121 3 necessitates necessitate VERB cana-572 121 4 dividing divide VERB cana-572 121 5 the the DET cana-572 121 6 dataset dataset NOUN cana-572 121 7 into into ADP cana-572 121 8 many many ADJ cana-572 121 9 folds fold NOUN cana-572 121 10 , , PUNCT cana-572 121 11 which which PRON cana-572 121 12 are be AUX cana-572 121 13 subsets subset NOUN cana-572 121 14 ; ; PUNCT cana-572 121 15 the the DET cana-572 121 16 model model NOUN cana-572 121 17 is be AUX cana-572 121 18 subsequently subsequently ADV cana-572 121 19 trained train VERB cana-572 121 20 on on ADP cana-572 121 21 a a DET cana-572 121 22 subset subset NOUN cana-572 121 23 of of ADP cana-572 121 24 the the DET cana-572 121 25 folds fold NOUN cana-572 121 26 and and CCONJ cana-572 121 27 assessed assess VERB cana-572 121 28 on on ADP cana-572 121 29 the the DET cana-572 121 30 remaining remain VERB cana-572 121 31 folds fold NOUN cana-572 121 32 . . PUNCT cana-572 122 1 each each DET cana-572 122 2 time time NOUN cana-572 122 3 this this DET cana-572 122 4 procedure procedure NOUN cana-572 122 5 is be AUX cana-572 122 6 replicated replicate VERB cana-572 122 7 , , PUNCT cana-572 122 8 distinct distinct ADJ cana-572 122 9 subsets subset NOUN cana-572 122 10 are be AUX cana-572 122 11 utilized utilize VERB cana-572 122 12 for for ADP cana-572 122 13 instruction instruction NOUN cana-572 122 14 and and CCONJ cana-572 122 15 evaluation evaluation NOUN cana-572 122 16 . . PUNCT cana-572 123 1 feature feature NOUN cana-572 123 2 selections selection VERB cana-572 123 3 the the DET cana-572 123 4 proposed propose VERB cana-572 123 5 study study NOUN cana-572 123 6 on on ADP cana-572 123 7 breast breast NOUN cana-572 123 8 cancer cancer NOUN cana-572 123 9 prediction prediction NOUN cana-572 123 10 using use VERB cana-572 123 11 supervised supervised ADJ cana-572 123 12 learning learning NOUN cana-572 123 13 methods method NOUN cana-572 123 14 , , PUNCT cana-572 123 15 feature feature NOUN cana-572 123 16 selection selection NOUN cana-572 123 17 plays play VERB cana-572 123 18 a a DET cana-572 123 19 crucial crucial ADJ cana-572 123 20 role role NOUN cana-572 123 21 in in ADP cana-572 123 22 identifying identify VERB cana-572 123 23 the the DET cana-572 123 24 most most ADV cana-572 123 25 relevant relevant ADJ cana-572 123 26 and and CCONJ cana-572 123 27 informative informative ADJ cana-572 123 28 features feature NOUN cana-572 123 29 from from ADP cana-572 123 30 the the DET cana-572 123 31 dataset dataset NOUN cana-572 123 32 . . PUNCT cana-572 124 1 effective effective ADJ cana-572 124 2 feature feature NOUN cana-572 124 3 selection selection NOUN cana-572 124 4 can can AUX cana-572 124 5 improve improve VERB cana-572 124 6 model model NOUN cana-572 124 7 performance performance NOUN cana-572 124 8 , , PUNCT cana-572 124 9 reduce reduce VERB cana-572 124 10 overfitting overfitting NOUN cana-572 124 11 , , PUNCT cana-572 124 12 and and CCONJ cana-572 124 13 enhance enhance VERB cana-572 124 14 interpretability interpretability NOUN cana-572 124 15 . . PUNCT cana-572 125 1 in in ADP cana-572 125 2 the the DET cana-572 125 3 context context NOUN cana-572 125 4 of of ADP cana-572 125 5 feature feature NOUN cana-572 125 6 selection selection NOUN cana-572 125 7 for for ADP cana-572 125 8 breast breast NOUN cana-572 125 9 cancer cancer NOUN cana-572 125 10 prediction prediction NOUN cana-572 125 11 , , PUNCT cana-572 125 12 both both DET cana-572 125 13 particle particle NOUN cana-572 125 14 swarm swarm NOUN cana-572 125 15 optimization optimization NOUN cana-572 125 16 ( ( PUNCT cana-572 125 17 pso pso NOUN cana-572 125 18 ) ) PUNCT cana-572 125 19 and and CCONJ cana-572 125 20 grey grey ADJ cana-572 125 21 wolf wolf PROPN cana-572 125 22 optimizer optimizer NOUN cana-572 125 23 ( ( PUNCT cana-572 125 24 gwo gwo PROPN cana-572 125 25 ) ) PUNCT cana-572 125 26 can can AUX cana-572 125 27 be be AUX cana-572 125 28 employed employ VERB cana-572 125 29 as as ADP cana-572 125 30 metaheuristic metaheuristic ADJ cana-572 125 31 algorithms algorithm NOUN cana-572 125 32 to to PART cana-572 125 33 efficiently efficiently ADV cana-572 125 34 search search VERB cana-572 125 35 for for ADP cana-572 125 36 the the DET cana-572 125 37 optimal optimal ADJ cana-572 125 38 subset subset NOUN cana-572 125 39 of of ADP cana-572 125 40 features feature NOUN cana-572 125 41 . . PUNCT cana-572 126 1 these these DET cana-572 126 2 algorithms algorithm NOUN cana-572 126 3 aim aim VERB cana-572 126 4 to to PART cana-572 126 5 select select VERB cana-572 126 6 the the DET cana-572 126 7 most most ADV cana-572 126 8 relevant relevant ADJ cana-572 126 9 features feature NOUN cana-572 126 10 while while SCONJ cana-572 126 11 minimizing minimize VERB cana-572 126 12 redundancy redundancy NOUN cana-572 126 13 , , PUNCT cana-572 126 14 thus thus ADV cana-572 126 15 improving improve VERB cana-572 126 16 the the DET cana-572 126 17 performance performance NOUN cana-572 126 18 of of ADP cana-572 126 19 the the DET cana-572 126 20 predictive predictive ADJ cana-572 126 21 models model NOUN cana-572 126 22 . . PUNCT cana-572 127 1 here here ADV cana-572 127 2 's be AUX cana-572 127 3 how how SCONJ cana-572 127 4 pso pso NOUN cana-572 127 5 and and CCONJ cana-572 127 6 gwo gwo PROPN cana-572 127 7 can can AUX cana-572 127 8 be be AUX cana-572 127 9 applied apply VERB cana-572 127 10 for for ADP cana-572 127 11 feature feature NOUN cana-572 127 12 selection selection NOUN cana-572 127 13 : : PUNCT cana-572 127 14 a a DET cana-572 127 15 - - PUNCT cana-572 127 16 particle particle NOUN cana-572 127 17 swarm swarm NOUN cana-572 127 18 optimization optimization NOUN cana-572 127 19 pso pso NOUN cana-572 128 1 [ [ X cana-572 128 2 29 29 NUM cana-572 128 3 ] ] PUNCT cana-572 128 4 is be AUX cana-572 128 5 metaheuristic metaheuristic ADJ cana-572 128 6 algorithms algorithm NOUN cana-572 128 7 that that PRON cana-572 128 8 illustrate illustrate VERB cana-572 128 9 inspiration inspiration NOUN cana-572 128 10 from from ADP cana-572 128 11 swarm swarm NOUN cana-572 128 12 performance performance NOUN cana-572 128 13 observed observe VERB cana-572 128 14 in in ADP cana-572 128 15 nature nature NOUN cana-572 128 16 , , PUNCT cana-572 128 17 specially specially ADV cana-572 128 18 the the DET cana-572 128 19 flocking flocking NOUN cana-572 128 20 of of ADP cana-572 128 21 birds bird NOUN cana-572 128 22 . . PUNCT cana-572 129 1 in in ADP cana-572 129 2 1995 1995 NUM cana-572 129 3 , , PUNCT cana-572 129 4 kennedy kennedy PROPN cana-572 129 5 and and CCONJ cana-572 129 6 eberhart eberhart PROPN cana-572 129 7 put put VERB cana-572 129 8 forth forth ADP cana-572 129 9 the the DET cana-572 129 10 proposition proposition NOUN cana-572 129 11 . . PUNCT cana-572 130 1 pso pso NOUN cana-572 130 2 is be AUX cana-572 130 3 a a DET cana-572 130 4 stochastic stochastic ADJ cana-572 130 5 optimization optimization NOUN cana-572 130 6 technique technique NOUN cana-572 130 7 that that PRON cana-572 130 8 manipulates manipulate VERB cana-572 130 9 populations population NOUN cana-572 130 10 and and CCONJ cana-572 130 11 draws draw VERB cana-572 130 12 inspiration inspiration NOUN cana-572 130 13 from from ADP cana-572 130 14 the the DET cana-572 130 15 social social ADJ cana-572 130 16 dynamics dynamic NOUN cana-572 130 17 observed observe VERB cana-572 130 18 in in ADP cana-572 130 19 fish fish NOUN cana-572 130 20 schooling schooling NOUN cana-572 130 21 or or CCONJ cana-572 130 22 avian avian ADJ cana-572 130 23 flocking flocking NOUN cana-572 130 24 . . PUNCT cana-572 131 1 the the DET cana-572 131 2 communications communication NOUN cana-572 131 3 on on ADP cana-572 131 4 applied apply VERB cana-572 131 5 nonlinear nonlinear ADJ cana-572 131 6 analysis analysis NOUN cana-572 131 7 issn issn NOUN cana-572 131 8 : : PUNCT cana-572 131 9 1074 1074 NUM cana-572 131 10 - - PUNCT cana-572 131 11 133x 133x NUM cana-572 131 12 vol vol NOUN cana-572 131 13 31 31 NUM cana-572 131 14 no no NOUN cana-572 131 15 . . NOUN cana-572 131 16 2 2 NUM cana-572 131 17 ( ( PUNCT cana-572 131 18 2024 2024 NUM cana-572 131 19 ) ) PUNCT cana-572 131 20 338 338 NUM cana-572 131 21 https://internationalpubls.com https://internationalpubls.com X cana-572 131 22 proposition proposition NOUN cana-572 131 23 was be AUX cana-572 131 24 initially initially ADV cana-572 131 25 put put VERB cana-572 131 26 forth forth ADP cana-572 131 27 in in ADP cana-572 131 28 1995 1995 NUM cana-572 131 29 by by ADP cana-572 131 30 kennedy kennedy PROPN cana-572 131 31 and and CCONJ cana-572 131 32 eberhart eberhart PROPN cana-572 131 33 . . PUNCT cana-572 132 1 pso pso NOUN cana-572 132 2 attempts attempt VERB cana-572 132 3 to to PART cana-572 132 4 improve improve VERB cana-572 132 5 the the DET cana-572 132 6 fitness fitness NOUN cana-572 132 7 of of ADP cana-572 132 8 a a DET cana-572 132 9 candidate candidate NOUN cana-572 132 10 solution solution NOUN cana-572 132 11 iteratively iteratively ADV cana-572 132 12 through through ADP cana-572 132 13 simulation simulation NOUN cana-572 132 14 of of ADP cana-572 132 15 the the DET cana-572 132 16 social social ADJ cana-572 132 17 behavior behavior NOUN cana-572 132 18 of of ADP cana-572 132 19 particles particle NOUN cana-572 132 20 traversing traverse VERB cana-572 132 21 a a DET cana-572 132 22 search search NOUN cana-572 132 23 space space NOUN cana-572 132 24 . . PUNCT cana-572 133 1 here here ADV cana-572 133 2 is be AUX cana-572 133 3 the the DET cana-572 133 4 typical typical ADJ cana-572 133 5 operation operation NOUN cana-572 133 6 of of ADP cana-572 133 7 pso pso NOUN cana-572 133 8 : : PUNCT cana-572 133 9 initialization initialization NOUN cana-572 133 10 : : PUNCT cana-572 133 11 particle particle NOUN cana-572 133 12 swarm swarm NOUN cana-572 133 13 optimization optimization NOUN cana-572 133 14 ( ( PUNCT cana-572 133 15 pso pso NOUN cana-572 133 16 ) ) PUNCT cana-572 133 17 starts start VERB cana-572 133 18 by by ADP cana-572 133 19 randomly randomly ADV cana-572 133 20 selecting select VERB cana-572 133 21 a a DET cana-572 133 22 population population NOUN cana-572 133 23 of of ADP cana-572 133 24 particles particle NOUN cana-572 133 25 to to PART cana-572 133 26 initially initially ADV cana-572 133 27 populate populate VERB cana-572 133 28 the the DET cana-572 133 29 search search NOUN cana-572 133 30 space space NOUN cana-572 133 31 . . PUNCT cana-572 134 1 within within ADP cana-572 134 2 the the DET cana-572 134 3 context context NOUN cana-572 134 4 of of ADP cana-572 134 5 the the DET cana-572 134 6 optimization optimization NOUN cana-572 134 7 problem problem NOUN cana-572 134 8 , , PUNCT cana-572 134 9 each each DET cana-572 134 10 particle particle NOUN cana-572 134 11 is be AUX cana-572 134 12 a a DET cana-572 134 13 potential potential ADJ cana-572 134 14 solution solution NOUN cana-572 134 15 . . PUNCT cana-572 135 1 velocity velocity NOUN cana-572 135 2 and and CCONJ cana-572 135 3 position position NOUN cana-572 135 4 update update NOUN cana-572 135 5 : : PUNCT cana-572 135 6 each each DET cana-572 135 7 time time NOUN cana-572 135 8 through through ADP cana-572 135 9 the the DET cana-572 135 10 loop loop NOUN cana-572 135 11 ( ( PUNCT cana-572 135 12 or or CCONJ cana-572 135 13 generation generation NOUN cana-572 135 14 ) ) PUNCT cana-572 135 15 , , PUNCT cana-572 135 16 each each DET cana-572 135 17 particle particle NOUN cana-572 135 18 's 's PART cana-572 135 19 speed speed NOUN cana-572 135 20 and and CCONJ cana-572 135 21 location location NOUN cana-572 135 22 are be AUX cana-572 135 23 changed change VERB cana-572 135 24 based base VERB cana-572 135 25 on on ADP cana-572 135 26 its its PRON cana-572 135 27 current current ADJ cana-572 135 28 speed speed NOUN cana-572 135 29 and and CCONJ cana-572 135 30 location location NOUN cana-572 135 31 as as ADV cana-572 135 32 well well ADV cana-572 135 33 as as ADP cana-572 135 34 the the DET cana-572 135 35 best good ADJ cana-572 135 36 locations location NOUN cana-572 135 37 found find VERB cana-572 135 38 by by ADP cana-572 135 39 it it PRON cana-572 135 40 and and CCONJ cana-572 135 41 its its PRON cana-572 135 42 neighbors neighbor NOUN cana-572 135 43 . . PUNCT cana-572 136 1 velocity velocity NOUN cana-572 136 2 update update NOUN cana-572 136 3 : : PUNCT cana-572 136 4 the the DET cana-572 136 5 following follow VERB cana-572 136 6 formula formula NOUN cana-572 136 7 is be AUX cana-572 136 8 used use VERB cana-572 136 9 to to PART cana-572 136 10 update update VERB cana-572 136 11 each each DET cana-572 136 12 particle particle NOUN cana-572 136 13 's 's PART cana-572 136 14 velocity velocity NOUN cana-572 136 15 : : PUNCT cana-572 136 16 𝑣𝑖j 𝑣𝑖j VERB cana-572 136 17 𝑑+1 𝑑+1 PROPN cana-572 136 18 = = SYM cana-572 136 19 𝑀𝑣𝑖j 𝑀𝑣𝑖j NUM cana-572 136 20 𝑑 𝑑 PROPN cana-572 136 21 + + ADP cana-572 136 22 𝑐1 𝑐1 NOUN cana-572 136 23 π‘Ÿ1[𝑝𝐡𝑒𝑠𝑑𝑖 π‘Ÿ1[𝑝𝐡𝑒𝑠𝑑𝑖 NOUN cana-572 136 24 j j PROPN cana-572 136 25 𝑑 𝑑 PROPN cana-572 136 26 βˆ’ βˆ’ PROPN cana-572 136 27 π‘₯ij π‘₯ij X cana-572 136 28 𝑑 𝑑 X cana-572 136 29 ] ] PUNCT cana-572 137 1 + + NUM cana-572 137 2 𝑐2 𝑐2 NOUN cana-572 137 3 π‘Ÿ2[𝑔𝐡𝑒𝑠𝑑𝑖j π‘Ÿ2[𝑔𝐡𝑒𝑠𝑑𝑖j NOUN cana-572 137 4 𝑑 𝑑 NOUN cana-572 137 5 βˆ’ βˆ’ NOUN cana-572 137 6 π‘₯ij π‘₯ij X cana-572 137 7 𝑑 𝑑 X cana-572 137 8 ] ] X cana-572 137 9 ( ( PUNCT cana-572 137 10 26 26 NUM cana-572 137 11 ) ) PUNCT cana-572 137 12 π‘₯𝑖j π‘₯𝑖j NOUN cana-572 138 1 𝑑+1 𝑑+1 NUM cana-572 138 2 = = PUNCT cana-572 138 3 π‘₯ij π‘₯ij X cana-572 138 4 𝑑 𝑑 X cana-572 138 5 + + X cana-572 138 6 𝑣𝑖j 𝑣𝑖j ADP cana-572 138 7 𝑑+1 𝑑+1 PROPN cana-572 138 8 ( ( PUNCT cana-572 138 9 27 27 NUM cana-572 138 10 ) ) PUNCT cana-572 138 11 𝑣𝑖j 𝑣𝑖j VERB cana-572 138 12 𝑑 𝑑 PROPN cana-572 138 13 is be AUX cana-572 138 14 velocity velocity NOUN cana-572 138 15 of of ADP cana-572 138 16 ith ith PROPN cana-572 138 17 partical partical PROPN cana-572 138 18 of of ADP cana-572 138 19 jth jth PROPN cana-572 138 20 dimension dimension NOUN cana-572 138 21 at at ADP cana-572 138 22 time time NOUN cana-572 138 23 t t PROPN cana-572 138 24 and and CCONJ cana-572 138 25 π‘₯𝑖j π‘₯𝑖j PRON cana-572 138 26 𝑑 𝑑 PROPN cana-572 138 27 is be AUX cana-572 138 28 position position NOUN cana-572 138 29 of of ADP cana-572 138 30 same same ADJ cana-572 138 31 , , PUNCT cana-572 138 32 w w PROPN cana-572 138 33 is be AUX cana-572 138 34 inertia inertia NOUN cana-572 138 35 weight weight NOUN cana-572 138 36 , , PUNCT cana-572 138 37 𝑐1 𝑐1 NOUN cana-572 138 38 𝑐2 𝑐2 NOUN cana-572 138 39 are be AUX cana-572 138 40 cognitive cognitive ADJ cana-572 138 41 learning learning NOUN cana-572 138 42 factor factor NOUN cana-572 138 43 , , PUNCT cana-572 138 44 π‘Ÿ1 π‘Ÿ1 NOUN cana-572 138 45 π‘Ÿ2 π‘Ÿ2 NOUN cana-572 138 46 uniformly uniformly ADV cana-572 138 47 distributed distribute VERB cana-572 138 48 random random ADJ cana-572 138 49 number number NOUN cana-572 138 50 between between ADP cana-572 138 51 0 0 NUM cana-572 138 52 and and CCONJ cana-572 138 53 1 1 NUM cana-572 138 54 , , PUNCT cana-572 138 55 pbest pbest NOUN cana-572 138 56 is be AUX cana-572 138 57 its its PRON cana-572 138 58 personal personal ADJ cana-572 138 59 best good ADJ cana-572 138 60 value value NOUN cana-572 138 61 and and CCONJ cana-572 138 62 gbest gbest NOUN cana-572 138 63 is be AUX cana-572 138 64 global global ADJ cana-572 138 65 best good ADJ cana-572 138 66 value value NOUN cana-572 138 67 . . PUNCT cana-572 139 1 then then ADV cana-572 139 2 position position NOUN cana-572 139 3 is be AUX cana-572 139 4 converted convert VERB cana-572 139 5 in in ADP cana-572 139 6 binary binary ADJ cana-572 139 7 using use VERB cana-572 139 8 sigmoid sigmoid NOUN cana-572 139 9 function function NOUN cana-572 139 10 . . PUNCT cana-572 140 1 π‘₯𝑖j π‘₯𝑖j VERB cana-572 140 2 𝑑+1= 𝑑+1= NOUN cana-572 140 3 { { PUNCT cana-572 140 4 0 0 NUM cana-572 140 5 𝑖𝑓 𝑖𝑓 NUM cana-572 140 6 π‘Ÿπ‘Žπ‘›π‘‘ π‘Ÿπ‘Žπ‘›π‘‘ NOUN cana-572 140 7 ( ( PUNCT cana-572 140 8 ) ) PUNCT cana-572 140 9 β‰₯ β‰₯ PROPN cana-572 140 10 sigmoid(𝑣𝑖j sigmoid(𝑣𝑖j PROPN cana-572 140 11 𝑑+1 𝑑+1 PROPN cana-572 140 12 ) ) PUNCT cana-572 140 13 1 1 NUM cana-572 140 14 𝑖𝑓 𝑖𝑓 ADP cana-572 140 15 π‘Ÿπ‘Žπ‘›π‘‘ π‘Ÿπ‘Žπ‘›π‘‘ NOUN cana-572 140 16 ( ( PUNCT cana-572 140 17 ) ) PUNCT cana-572 140 18 < < X cana-572 140 19 sigmoid(𝑣𝑖j sigmoid(𝑣𝑖j PROPN cana-572 140 20 𝑑+1 𝑑+1 NOUN cana-572 140 21 ) ) PUNCT cana-572 140 22 ( ( PUNCT cana-572 140 23 28 28 NUM cana-572 140 24 ) ) PUNCT cana-572 140 25 sigmoid sigmoid NOUN cana-572 140 26 ( ( PUNCT cana-572 140 27 𝑣𝑖j 𝑣𝑖j ADP cana-572 140 28 𝑑+1 𝑑+1 NOUN cana-572 140 29 ) ) PUNCT cana-572 140 30 = = SYM cana-572 140 31 1 1 NUM cana-572 140 32 / / SYM cana-572 140 33 ( ( PUNCT cana-572 140 34 1+π‘’βˆ’π‘£π‘–j 1+π‘’βˆ’π‘£π‘–j NUM cana-572 140 35 𝑑 𝑑 NOUN cana-572 140 36 ) ) PUNCT cana-572 140 37 ( ( PUNCT cana-572 140 38 29 29 NUM cana-572 140 39 ) ) PUNCT cana-572 140 40 where where SCONJ cana-572 140 41 rand rand NOUN cana-572 140 42 ( ( PUNCT cana-572 140 43 ) ) PUNCT cana-572 140 44 is be AUX cana-572 140 45 a a DET cana-572 140 46 random random ADJ cana-572 140 47 number number NOUN cana-572 140 48 between between ADP cana-572 140 49 0 0 NUM cana-572 140 50 and and CCONJ cana-572 140 51 1 1 NUM cana-572 140 52 , , PUNCT cana-572 140 53 and and CCONJ cana-572 140 54 the the DET cana-572 140 55 sigmoid sigmoid NOUN cana-572 140 56 function function NOUN cana-572 140 57 transforms transform VERB cana-572 140 58 the the DET cana-572 140 59 velocity velocity NOUN cana-572 140 60 value value NOUN cana-572 140 61 into into ADP cana-572 140 62 a a DET cana-572 140 63 probability probability NOUN cana-572 140 64 between between ADP cana-572 140 65 0 0 NUM cana-572 140 66 and and CCONJ cana-572 140 67 1 1 NUM cana-572 140 68 evaluation evaluation NOUN cana-572 140 69 : : PUNCT cana-572 140 70 after after ADP cana-572 140 71 updating update VERB cana-572 140 72 the the DET cana-572 140 73 positions position NOUN cana-572 140 74 , , PUNCT cana-572 140 75 the the DET cana-572 140 76 fitness fitness NOUN cana-572 140 77 of of ADP cana-572 140 78 each each DET cana-572 140 79 particle particle NOUN cana-572 140 80 is be AUX cana-572 140 81 evaluated evaluate VERB cana-572 140 82 based base VERB cana-572 140 83 on on ADP cana-572 140 84 the the DET cana-572 140 85 objective objective ADJ cana-572 140 86 function function NOUN cana-572 140 87 of of ADP cana-572 140 88 the the DET cana-572 140 89 optimization optimization NOUN cana-572 140 90 problem problem NOUN cana-572 140 91 . . PUNCT cana-572 141 1 update update VERB cana-572 141 2 personal personal ADJ cana-572 141 3 and and CCONJ cana-572 141 4 global global ADJ cana-572 141 5 best good ADJ cana-572 141 6 : : PUNCT cana-572 141 7 it it PRON cana-572 141 8 is be AUX cana-572 141 9 possible possible ADJ cana-572 141 10 for for SCONJ cana-572 141 11 each each DET cana-572 141 12 particle particle NOUN cana-572 141 13 to to PART cana-572 141 14 change change VERB cana-572 141 15 its its PRON cana-572 141 16 personal personal ADJ cana-572 141 17 best good ADJ cana-572 141 18 position position NOUN cana-572 141 19 ( ( PUNCT cana-572 141 20 pbest pbest NOUN cana-572 141 21 ) ) PUNCT cana-572 141 22 if if SCONJ cana-572 141 23 the the DET cana-572 141 24 new new ADJ cana-572 141 25 position position NOUN cana-572 141 26 makes make VERB cana-572 141 27 it it PRON cana-572 141 28 more more ADV cana-572 141 29 fit fit ADJ cana-572 141 30 . . PUNCT cana-572 142 1 also also ADV cana-572 142 2 , , PUNCT cana-572 142 3 if if SCONJ cana-572 142 4 a a DET cana-572 142 5 particle particle NOUN cana-572 142 6 finds find VERB cana-572 142 7 a a DET cana-572 142 8 better well ADJ cana-572 142 9 answer answer NOUN cana-572 142 10 than than ADP cana-572 142 11 the the DET cana-572 142 12 current current ADJ cana-572 142 13 global global ADJ cana-572 142 14 best good ADJ cana-572 142 15 , , PUNCT cana-572 142 16 it it PRON cana-572 142 17 changes change VERB cana-572 142 18 the the DET cana-572 142 19 global global ADJ cana-572 142 20 best good ADJ cana-572 142 21 position position NOUN cana-572 142 22 ( ( PUNCT cana-572 142 23 gbest gbest NOUN cana-572 142 24 ) ) PUNCT cana-572 142 25 . . PUNCT cana-572 143 1 termination termination NOUN cana-572 143 2 : : PUNCT cana-572 144 1 pso pso NOUN cana-572 144 2 iterates iterate VERB cana-572 144 3 indefinitely indefinitely ADV cana-572 144 4 until until SCONJ cana-572 144 5 a a DET cana-572 144 6 termination termination NOUN cana-572 144 7 condition condition NOUN cana-572 144 8 is be AUX cana-572 144 9 satisfied satisfied ADJ cana-572 144 10 , , PUNCT cana-572 144 11 which which PRON cana-572 144 12 may may AUX cana-572 144 13 be be AUX cana-572 144 14 the the DET cana-572 144 15 attainment attainment NOUN cana-572 144 16 of of ADP cana-572 144 17 a a DET cana-572 144 18 satisfactory satisfactory ADJ cana-572 144 19 solution solution NOUN cana-572 144 20 or or CCONJ cana-572 144 21 the the DET cana-572 144 22 completion completion NOUN cana-572 144 23 of of ADP cana-572 144 24 a a DET cana-572 144 25 limit limit NOUN cana-572 144 26 number number NOUN cana-572 144 27 of of ADP cana-572 144 28 iterations iteration NOUN cana-572 144 29 . . PUNCT cana-572 145 1 b b X cana-572 145 2 - - PUNCT cana-572 145 3 grey grey ADJ cana-572 145 4 wolf wolf PROPN cana-572 145 5 optimizer optimizer NOUN cana-572 145 6 ( ( PUNCT cana-572 145 7 gwo gwo NOUN cana-572 145 8 ) ) PUNCT cana-572 145 9 grey grey ADJ cana-572 145 10 wolf wolf PROPN cana-572 145 11 optimizer optimizer NOUN cana-572 145 12 ( ( PUNCT cana-572 145 13 gwo gwo PROPN cana-572 145 14 ) ) PUNCT cana-572 145 15 a a DET cana-572 145 16 population population NOUN cana-572 145 17 - - PUNCT cana-572 145 18 based base VERB cana-572 145 19 metaheuristic metaheuristic ADJ cana-572 145 20 optimization optimization NOUN cana-572 145 21 method method NOUN cana-572 145 22 was be AUX cana-572 145 23 created create VERB cana-572 145 24 by by ADP cana-572 145 25 looking look VERB cana-572 145 26 at at ADP cana-572 145 27 the the DET cana-572 145 28 social social ADJ cana-572 145 29 structure structure NOUN cana-572 145 30 and and CCONJ cana-572 145 31 hunting hunt VERB cana-572 145 32 habits habit NOUN cana-572 145 33 of of ADP cana-572 145 34 grey grey ADJ cana-572 145 35 wolves wolf NOUN cana-572 145 36 . . PUNCT cana-572 146 1 as as ADP cana-572 146 2 an an DET cana-572 146 3 alternate alternate ADJ cana-572 146 4 optimization optimization NOUN cana-572 146 5 technique technique NOUN cana-572 146 6 for for ADP cana-572 146 7 the the DET cana-572 146 8 purpose purpose NOUN cana-572 146 9 of of ADP cana-572 146 10 resolving resolve VERB cana-572 146 11 complex complex ADJ cana-572 146 12 optimization optimization NOUN cana-572 146 13 issues issue NOUN cana-572 146 14 , , PUNCT cana-572 146 15 gwo gwo PROPN cana-572 146 16 was be AUX cana-572 146 17 presented present VERB cana-572 146 18 by by ADP cana-572 146 19 mirjalili mirjalili PROPN cana-572 146 20 et et PROPN cana-572 146 21 al al PROPN cana-572 146 22 . . PROPN cana-572 146 23 in in ADP cana-572 146 24 the the DET cana-572 146 25 year year NOUN cana-572 146 26 2014.'[26 2014.'[26 NUM cana-572 146 27 ] ] PUNCT cana-572 146 28 communications communication NOUN cana-572 146 29 on on ADP cana-572 146 30 applied apply VERB cana-572 146 31 nonlinear nonlinear ADJ cana-572 146 32 analysis analysis NOUN cana-572 146 33 issn issn NOUN cana-572 146 34 : : PUNCT cana-572 146 35 1074 1074 NUM cana-572 146 36 - - PUNCT cana-572 146 37 133x 133x NUM cana-572 146 38 vol vol NOUN cana-572 146 39 31 31 NUM cana-572 146 40 no no NOUN cana-572 146 41 . . NOUN cana-572 146 42 2 2 NUM cana-572 146 43 ( ( PUNCT cana-572 146 44 2024 2024 NUM cana-572 146 45 ) ) PUNCT cana-572 147 1 339 339 NUM cana-572 147 2 https://internationalpubls.com https://internationalpubls.com X cana-572 147 3 initialization initialization NOUN cana-572 147 4 : : PUNCT cana-572 147 5 at at ADP cana-572 147 6 the the DET cana-572 147 7 start start NOUN cana-572 147 8 , , PUNCT cana-572 147 9 gwo gwo PROPN cana-572 147 10 creates create VERB cana-572 147 11 a a DET cana-572 147 12 population population NOUN cana-572 147 13 of of ADP cana-572 147 14 possible possible ADJ cana-572 147 15 answers answer NOUN cana-572 147 16 at at ADP cana-572 147 17 random random ADJ cana-572 147 18 , , PUNCT cana-572 147 19 which which PRON cana-572 147 20 is be AUX cana-572 147 21 shown show VERB cana-572 147 22 as as ADP cana-572 147 23 a a DET cana-572 147 24 pack pack NOUN cana-572 147 25 of of ADP cana-572 147 26 grey grey ADJ cana-572 147 27 wolves wolf NOUN cana-572 147 28 . . PUNCT cana-572 148 1 hierarchy hierarchy NOUN cana-572 148 2 formation formation NOUN cana-572 148 3 : : PUNCT cana-572 148 4 based base VERB cana-572 148 5 on on ADP cana-572 148 6 their their PRON cana-572 148 7 fitness fitness NOUN cana-572 148 8 values value NOUN cana-572 148 9 , , PUNCT cana-572 148 10 the the DET cana-572 148 11 grey grey ADJ cana-572 148 12 wolves wolf NOUN cana-572 148 13 are be AUX cana-572 148 14 classified classify VERB cana-572 148 15 as as ADP cana-572 148 16 alpha alpha NOUN cana-572 148 17 , , PUNCT cana-572 148 18 beta beta NOUN cana-572 148 19 , , PUNCT cana-572 148 20 delta delta NOUN cana-572 148 21 , , PUNCT cana-572 148 22 or or CCONJ cana-572 148 23 omega omega NOUN cana-572 148 24 wolves wolf NOUN cana-572 148 25 in in ADP cana-572 148 26 each each DET cana-572 148 27 iteration iteration NOUN cana-572 148 28 . . PUNCT cana-572 149 1 the the DET cana-572 149 2 alpha alpha NOUN cana-572 149 3 wolf wolf PROPN cana-572 149 4 symbolizes symbolize VERB cana-572 149 5 the the DET cana-572 149 6 most most ADV cana-572 149 7 optimal optimal ADJ cana-572 149 8 solution solution NOUN cana-572 149 9 thus thus ADV cana-572 149 10 far far ADV cana-572 149 11 , , PUNCT cana-572 149 12 while while SCONJ cana-572 149 13 the the DET cana-572 149 14 beta beta ADJ cana-572 149 15 wolf wolf NOUN cana-572 149 16 and and CCONJ cana-572 149 17 delta delta PROPN cana-572 149 18 wolf wolf PROPN cana-572 149 19 represent represent VERB cana-572 149 20 the the DET cana-572 149 21 second second ADV cana-572 149 22 - - PUNCT cana-572 149 23 best good ADJ cana-572 149 24 and and CCONJ cana-572 149 25 third third ADV cana-572 149 26 - - PUNCT cana-572 149 27 best good ADJ cana-572 149 28 solutions solution NOUN cana-572 149 29 , , PUNCT cana-572 149 30 respectively respectively ADV cana-572 149 31 . . PUNCT cana-572 150 1 the the DET cana-572 150 2 omega omega NOUN cana-572 150 3 wolf wolf NOUN cana-572 150 4 denotes denote VERB cana-572 150 5 the the DET cana-572 150 6 worst bad ADJ cana-572 150 7 solution solution NOUN cana-572 150 8 thus thus ADV cana-572 150 9 far far ADV cana-572 150 10 . . PUNCT cana-572 151 1 update update NOUN cana-572 151 2 positions position NOUN cana-572 151 3 : : PUNCT cana-572 151 4 to to PART cana-572 151 5 simulate simulate VERB cana-572 151 6 the the DET cana-572 151 7 way way NOUN cana-572 151 8 that that PRON cana-572 151 9 wolves wolf NOUN cana-572 151 10 hunt hunt VERB cana-572 151 11 , , PUNCT cana-572 151 12 each each DET cana-572 151 13 individual individual ADJ cana-572 151 14 wolf wolf PROPN cana-572 151 15 will will AUX cana-572 151 16 modify modify VERB cana-572 151 17 its its PRON cana-572 151 18 position position NOUN cana-572 151 19 in in ADP cana-572 151 20 accordance accordance NOUN cana-572 151 21 with with ADP cana-572 151 22 the the DET cana-572 151 23 positions position NOUN cana-572 151 24 of of ADP cana-572 151 25 the the DET cana-572 151 26 alpha alpha NOUN cana-572 151 27 , , PUNCT cana-572 151 28 beta beta NOUN cana-572 151 29 , , PUNCT cana-572 151 30 and and CCONJ cana-572 151 31 delta delta NOUN cana-572 151 32 wolves wolf NOUN cana-572 151 33 . . PUNCT cana-572 152 1 this this PRON cana-572 152 2 is be AUX cana-572 152 3 done do VERB cana-572 152 4 using use VERB cana-572 152 5 specific specific ADJ cana-572 152 6 equations equation NOUN cana-572 152 7 that that PRON cana-572 152 8 determine determine VERB cana-572 152 9 the the DET cana-572 152 10 movement movement NOUN cana-572 152 11 of of ADP cana-572 152 12 each each DET cana-572 152 13 wolf wolf NOUN cana-572 152 14 towards towards ADP cana-572 152 15 the the DET cana-572 152 16 alpha alpha NOUN cana-572 152 17 , , PUNCT cana-572 152 18 beta beta NOUN cana-572 152 19 , , PUNCT cana-572 152 20 and and CCONJ cana-572 152 21 delta delta NOUN cana-572 152 22 wolves wolf NOUN cana-572 152 23 , , PUNCT cana-572 152 24 as as ADV cana-572 152 25 well well ADV cana-572 152 26 as as ADP cana-572 152 27 exploration exploration NOUN cana-572 152 28 and and CCONJ cana-572 152 29 exploitation exploitation NOUN cana-572 152 30 phases phase NOUN cana-572 152 31 . . PUNCT cana-572 153 1 fitness fitness NOUN cana-572 153 2 evaluation evaluation NOUN cana-572 153 3 : : PUNCT cana-572 153 4 the the DET cana-572 153 5 fitness fitness NOUN cana-572 153 6 of of ADP cana-572 153 7 each each DET cana-572 153 8 wolf wolf NOUN cana-572 153 9 is be AUX cana-572 153 10 evaluated evaluate VERB cana-572 153 11 based base VERB cana-572 153 12 on on ADP cana-572 153 13 the the DET cana-572 153 14 objective objective ADJ cana-572 153 15 function function NOUN cana-572 153 16 of of ADP cana-572 153 17 the the DET cana-572 153 18 optimization optimization NOUN cana-572 153 19 problem problem NOUN cana-572 153 20 after after SCONJ cana-572 153 21 their their PRON cana-572 153 22 positions position NOUN cana-572 153 23 have have AUX cana-572 153 24 been be AUX cana-572 153 25 updated update VERB cana-572 153 26 by by ADP cana-572 153 27 the the DET cana-572 153 28 algorithm algorithm NOUN cana-572 153 29 . . PUNCT cana-572 154 1 update update NOUN cana-572 154 2 alpha alpha NOUN cana-572 154 3 , , PUNCT cana-572 154 4 beta beta NOUN cana-572 154 5 , , PUNCT cana-572 154 6 and and CCONJ cana-572 154 7 delta delta NOUN cana-572 154 8 wolves wolf NOUN cana-572 154 9 : : PUNCT cana-572 154 10 the the DET cana-572 154 11 fitness fitness NOUN cana-572 154 12 of of ADP cana-572 154 13 the the DET cana-572 154 14 wolves wolf NOUN cana-572 154 15 in in ADP cana-572 154 16 the the DET cana-572 154 17 current current ADJ cana-572 154 18 cycle cycle NOUN cana-572 154 19 is be AUX cana-572 154 20 used use VERB cana-572 154 21 to to PART cana-572 154 22 change change VERB cana-572 154 23 the the DET cana-572 154 24 alpha alpha NOUN cana-572 154 25 , , PUNCT cana-572 154 26 beta beta NOUN cana-572 154 27 , , PUNCT cana-572 154 28 and and CCONJ cana-572 154 29 delta delta NOUN cana-572 154 30 wolves wolf NOUN cana-572 154 31 . . PUNCT cana-572 155 1 if if SCONJ cana-572 155 2 another another DET cana-572 155 3 wolf wolf NOUN cana-572 155 4 comes come VERB cana-572 155 5 up up ADP cana-572 155 6 with with ADP cana-572 155 7 a a DET cana-572 155 8 better well ADJ cana-572 155 9 idea idea NOUN cana-572 155 10 than than ADP cana-572 155 11 the the DET cana-572 155 12 current current ADJ cana-572 155 13 alpha alpha NOUN cana-572 155 14 , , PUNCT cana-572 155 15 beta beta NOUN cana-572 155 16 , , PUNCT cana-572 155 17 or or CCONJ cana-572 155 18 delta delta NOUN cana-572 155 19 wolf wolf PROPN cana-572 155 20 , , PUNCT cana-572 155 21 it it PRON cana-572 155 22 takes take VERB cana-572 155 23 their their PRON cana-572 155 24 place place NOUN cana-572 155 25 . . PUNCT cana-572 156 1 d d X cana-572 156 2 = = PUNCT cana-572 156 3 |cxp |cxp PROPN cana-572 156 4 βˆ’ βˆ’ NOUN cana-572 156 5 ax ax NOUN cana-572 156 6 ( ( PUNCT cana-572 156 7 t)| t)| NOUN cana-572 156 8 ( ( PUNCT cana-572 156 9 30 30 NUM cana-572 156 10 ) ) PUNCT cana-572 156 11 x x X cana-572 156 12 ( ( PUNCT cana-572 156 13 t t NOUN cana-572 156 14 + + NOUN cana-572 156 15 1 1 NUM cana-572 156 16 ) ) PUNCT cana-572 156 17 = = PRON cana-572 156 18 xp xp X cana-572 156 19 ( ( PUNCT cana-572 156 20 t t PROPN cana-572 156 21 ) ) PUNCT cana-572 156 22 βˆ’ βˆ’ PROPN cana-572 157 1 ad ad NOUN cana-572 157 2 ( ( PUNCT cana-572 157 3 31 31 NUM cana-572 157 4 ) ) PUNCT cana-572 157 5 xp xp X cana-572 157 6 is be AUX cana-572 157 7 position position NOUN cana-572 157 8 of of ADP cana-572 157 9 prey prey NOUN cana-572 157 10 at at ADP cana-572 157 11 current current ADJ cana-572 157 12 iteration iteration NOUN cana-572 157 13 t t PROPN cana-572 157 14 , , PUNCT cana-572 157 15 x x X cana-572 157 16 is be AUX cana-572 157 17 the the DET cana-572 157 18 position position NOUN cana-572 157 19 vector vector NOUN cana-572 157 20 of of ADP cana-572 157 21 a a DET cana-572 157 22 wolf wolf NOUN cana-572 157 23 , , PUNCT cana-572 157 24 a a PRON cana-572 157 25 and and CCONJ cana-572 157 26 c c NOUN cana-572 157 27 are be AUX cana-572 157 28 coefficient coefficient ADJ cana-572 157 29 vectors vector NOUN cana-572 157 30 given give VERB cana-572 157 31 as as ADP cana-572 157 32 : : PUNCT cana-572 157 33 a=2ar1 a=2ar1 PROPN cana-572 157 34 - - PUNCT cana-572 157 35 a a DET cana-572 157 36 c=2r2 c=2r2 PROPN cana-572 157 37 r1 r1 NOUN cana-572 157 38 and and CCONJ cana-572 157 39 r2 r2 PROPN cana-572 157 40 are be AUX cana-572 157 41 random random ADJ cana-572 157 42 vectors vector NOUN cana-572 157 43 ∈ ∈ NOUN cana-572 158 1 [ [ X cana-572 158 2 0 0 NUM cana-572 158 3 , , PUNCT cana-572 158 4 1 1 NUM cana-572 158 5 ] ] PUNCT cana-572 158 6 and and CCONJ cana-572 158 7 a a DET cana-572 158 8 linearly linearly ADV cana-572 158 9 varies vary VERB cana-572 158 10 from from ADP cana-572 158 11 2 2 NUM cana-572 158 12 to to ADP cana-572 158 13 0 0 NUM cana-572 158 14 dΞ± dΞ± ADJ cana-572 158 15 = = PUNCT cana-572 158 16 |c1.xΞ± |c1.xΞ± NOUN cana-572 158 17 x| x| NOUN cana-572 158 18 , , PUNCT cana-572 158 19 dΞ² dΞ² ADJ cana-572 158 20 = = NOUN cana-572 158 21 |c2.xΞ² |c2.xΞ² X cana-572 158 22 x| x| PROPN cana-572 158 23 , , PUNCT cana-572 158 24 dΞ΄ dΞ΄ ADP cana-572 158 25 = = PUNCT cana-572 158 26 |c3.xΞ΄ |c3.xΞ΄ PROPN cana-572 158 27 – – PUNCT cana-572 158 28 x| x| NOUN cana-572 158 29 ( ( PUNCT cana-572 158 30 32 32 NUM cana-572 158 31 ) ) PUNCT cana-572 158 32 x1= x1= PROPN cana-572 158 33 xΞ± xΞ± PROPN cana-572 158 34 – – PUNCT cana-572 158 35 a1 a1 NOUN cana-572 158 36 dΞ± dΞ± NOUN cana-572 158 37 , , PUNCT cana-572 158 38 x2 x2 PROPN cana-572 158 39 = = SYM cana-572 158 40 xΞ² xΞ² ADV cana-572 158 41 – – PUNCT cana-572 158 42 a2dΞ² a2dΞ² X cana-572 158 43 , , PUNCT cana-572 158 44 x3 x3 PROPN cana-572 158 45 = = SYM cana-572 158 46 xΞ΄ xΞ΄ PROPN cana-572 158 47 – – PUNCT cana-572 158 48 a3dΞ΄ a3dΞ΄ PUNCT cana-572 158 49 ( ( PUNCT cana-572 158 50 33 33 NUM cana-572 158 51 ) ) PUNCT cana-572 158 52 x x X cana-572 158 53 ( ( PUNCT cana-572 158 54 t t NOUN cana-572 158 55 + + CCONJ cana-572 158 56 1 1 NUM cana-572 158 57 ) ) PUNCT cana-572 158 58 = = NOUN cana-572 158 59 ( ( PUNCT cana-572 158 60 x1 x1 PROPN cana-572 158 61 + + PROPN cana-572 158 62 x2 x2 ADJ cana-572 158 63 + + CCONJ cana-572 158 64 x3 x3 ADJ cana-572 158 65 ) ) PUNCT cana-572 158 66 ( ( PUNCT cana-572 158 67 34 34 NUM cana-572 158 68 ) ) PUNCT cana-572 158 69 as as SCONJ cana-572 158 70 it it PRON cana-572 158 71 go go VERB cana-572 158 72 through through ADP cana-572 158 73 the the DET cana-572 158 74 iterations iteration NOUN cana-572 158 75 , , PUNCT cana-572 158 76 a a DET cana-572 158 77 changes change NOUN cana-572 158 78 from from ADP cana-572 158 79 2 2 NUM cana-572 158 80 to to ADP cana-572 158 81 0 0 NUM cana-572 158 82 , , PUNCT cana-572 158 83 which which PRON cana-572 158 84 is be AUX cana-572 158 85 the the DET cana-572 158 86 linear linear ADJ cana-572 158 87 value value NOUN cana-572 158 88 of of ADP cana-572 158 89 the the DET cana-572 158 90 Ξ± Ξ± PROPN cana-572 158 91 , , PUNCT cana-572 158 92 Ξ² Ξ² NOUN cana-572 158 93 , , PUNCT cana-572 158 94 and and CCONJ cana-572 158 95 Ξ΅ Ξ΅ PROPN cana-572 158 96 wolfs wolfs PROPN cana-572 158 97 . . PUNCT cana-572 159 1 termination termination NOUN cana-572 159 2 : : PUNCT cana-572 159 3 the the DET cana-572 159 4 algorithm algorithm NOUN cana-572 159 5 will will AUX cana-572 159 6 continue continue VERB cana-572 159 7 to to PART cana-572 159 8 iterate iterate VERB cana-572 159 9 until until SCONJ cana-572 159 10 a a DET cana-572 159 11 termination termination NOUN cana-572 159 12 condition condition NOUN cana-572 159 13 is be AUX cana-572 159 14 satisfied satisfied ADJ cana-572 159 15 , , PUNCT cana-572 159 16 which which PRON cana-572 159 17 could could AUX cana-572 159 18 be be AUX cana-572 159 19 reaching reach VERB cana-572 159 20 a a DET cana-572 159 21 maximum maximum ADJ cana-572 159 22 number number NOUN cana-572 159 23 of of ADP cana-572 159 24 iterations iteration NOUN cana-572 159 25 or or CCONJ cana-572 159 26 achieving achieve VERB cana-572 159 27 a a DET cana-572 159 28 solution solution NOUN cana-572 159 29 that that PRON cana-572 159 30 is be AUX cana-572 159 31 satisfactory satisfactory ADJ cana-572 159 32 . . PUNCT cana-572 160 1 communications communication NOUN cana-572 160 2 on on ADP cana-572 160 3 applied apply VERB cana-572 160 4 nonlinear nonlinear ADJ cana-572 160 5 analysis analysis NOUN cana-572 160 6 issn issn NOUN cana-572 160 7 : : PUNCT cana-572 160 8 1074 1074 NUM cana-572 160 9 - - PUNCT cana-572 160 10 133x 133x NUM cana-572 160 11 vol vol NOUN cana-572 160 12 31 31 NUM cana-572 160 13 no no NOUN cana-572 160 14 . . NOUN cana-572 160 15 2 2 NUM cana-572 160 16 ( ( PUNCT cana-572 160 17 2024 2024 NUM cana-572 160 18 ) ) PUNCT cana-572 160 19 340 340 NUM cana-572 160 20 https://internationalpubls.com https://internationalpubls.com X cana-572 160 21 c c X cana-572 160 22 - - PUNCT cana-572 160 23 hybrid hybrid ADJ cana-572 160 24 algorithm algorithm NOUN cana-572 160 25 a a DET cana-572 160 26 hybrid hybrid ADJ cana-572 160 27 algorithm algorithm NOUN cana-572 160 28 that that PRON cana-572 160 29 combines combine VERB cana-572 160 30 pso pso NOUN cana-572 160 31 and and CCONJ cana-572 160 32 gwo gwo VERB cana-572 160 33 for for ADP cana-572 160 34 breast breast NOUN cana-572 160 35 cancer cancer NOUN cana-572 160 36 detection detection NOUN cana-572 160 37 involves involve VERB cana-572 160 38 integrating integrate VERB cana-572 160 39 the the DET cana-572 160 40 search search NOUN cana-572 160 41 mechanisms mechanism NOUN cana-572 160 42 of of ADP cana-572 160 43 both both DET cana-572 160 44 algorithms algorithm NOUN cana-572 160 45 . . PUNCT cana-572 161 1 here here ADV cana-572 161 2 's be AUX cana-572 161 3 a a DET cana-572 161 4 conceptual conceptual ADJ cana-572 161 5 outline outline NOUN cana-572 161 6 along along ADP cana-572 161 7 with with ADP cana-572 161 8 mathematical mathematical ADJ cana-572 161 9 expressions expression NOUN cana-572 161 10 : : PUNCT cana-572 161 11 initialization initialization NOUN cana-572 161 12 : : PUNCT cana-572 161 13 initialize initialize VERB cana-572 161 14 the the DET cana-572 161 15 population population NOUN cana-572 161 16 of of ADP cana-572 161 17 particles particle NOUN cana-572 161 18 for for ADP cana-572 161 19 pso pso NOUN cana-572 161 20 and and CCONJ cana-572 161 21 the the DET cana-572 161 22 pack pack NOUN cana-572 161 23 of of ADP cana-572 161 24 wolves wolf NOUN cana-572 161 25 for for ADP cana-572 161 26 gwo gwo PROPN cana-572 161 27 randomly randomly ADV cana-572 161 28 within within ADP cana-572 161 29 the the DET cana-572 161 30 search search NOUN cana-572 161 31 space space NOUN cana-572 161 32 . . PUNCT cana-572 162 1 objective objective ADJ cana-572 162 2 function function NOUN cana-572 162 3 : : PUNCT cana-572 162 4 the the DET cana-572 162 5 objective objective ADJ cana-572 162 6 function function NOUN cana-572 162 7 that that PRON cana-572 162 8 represents represent VERB cana-572 162 9 the the DET cana-572 162 10 fitness fitness NOUN cana-572 162 11 of of ADP cana-572 162 12 a a DET cana-572 162 13 solution solution NOUN cana-572 162 14 based base VERB cana-572 162 15 on on ADP cana-572 162 16 its its PRON cana-572 162 17 ability ability NOUN cana-572 162 18 to to PART cana-572 162 19 classify classify VERB cana-572 162 20 breast breast NOUN cana-572 162 21 cancer cancer NOUN cana-572 162 22 accurately accurately ADV cana-572 162 23 . . PUNCT cana-572 163 1 precision precision NOUN cana-572 163 2 , , PUNCT cana-572 163 3 specificity specificity NOUN cana-572 163 4 , , PUNCT cana-572 163 5 sensitivity sensitivity NOUN cana-572 163 6 , , PUNCT cana-572 163 7 and and CCONJ cana-572 163 8 the the DET cana-572 163 9 roc roc PROPN cana-572 163 10 area area NOUN cana-572 163 11 are be AUX cana-572 163 12 just just ADV cana-572 163 13 a a DET cana-572 163 14 few few ADJ cana-572 163 15 of of ADP cana-572 163 16 the the DET cana-572 163 17 possible possible ADJ cana-572 163 18 factors factor NOUN cana-572 163 19 that that PRON cana-572 163 20 might might AUX cana-572 163 21 be be AUX cana-572 163 22 incorporated incorporate VERB cana-572 163 23 into into ADP cana-572 163 24 this this DET cana-572 163 25 function function NOUN cana-572 163 26 . . PUNCT cana-572 164 1 gwo gwo PROPN cana-572 164 2 position position NOUN cana-572 164 3 update update NOUN cana-572 164 4 equations equation NOUN cana-572 164 5 they they PRON cana-572 164 6 do do AUX cana-572 164 7 not not PART cana-572 164 8 make make VERB cana-572 164 9 use use NOUN cana-572 164 10 of of ADP cana-572 164 11 traditional traditional ADJ cana-572 164 12 mathematical mathematical ADJ cana-572 164 13 formulae formulae NOUN cana-572 164 14 ; ; PUNCT cana-572 164 15 rather rather ADV cana-572 164 16 , , PUNCT cana-572 164 17 we we PRON cana-572 164 18 make make VERB cana-572 164 19 use use NOUN cana-572 164 20 of of ADP cana-572 164 21 the the DET cana-572 164 22 inertia inertia NOUN cana-572 164 23 constant constant ADJ cana-572 164 24 to to PART cana-572 164 25 guide guide VERB cana-572 164 26 the the DET cana-572 164 27 exploration exploration NOUN cana-572 164 28 and and CCONJ cana-572 164 29 exploitation exploitation NOUN cana-572 164 30 of of ADP cana-572 164 31 the the DET cana-572 164 32 grey grey ADJ cana-572 164 33 wolf wolf NOUN cana-572 164 34 within within ADP cana-572 164 35 the the DET cana-572 164 36 bounds bound NOUN cana-572 164 37 of of ADP cana-572 164 38 the the DET cana-572 164 39 search search NOUN cana-572 164 40 space space NOUN cana-572 164 41 . . PUNCT cana-572 165 1 equation equation NOUN cana-572 165 2 ( ( PUNCT cana-572 165 3 5 5 NUM cana-572 165 4 ) ) PUNCT cana-572 165 5 , , PUNCT cana-572 165 6 after after ADP cana-572 165 7 being be AUX cana-572 165 8 modified modify VERB cana-572 165 9 , , PUNCT cana-572 165 10 is be AUX cana-572 165 11 now now ADV cana-572 165 12 the the DET cana-572 165 13 following following NOUN cana-572 165 14 : : PUNCT cana-572 165 15 dΞ± dΞ± ADJ cana-572 165 16 = = NOUN cana-572 165 17 |c1.xΞ± |c1.xΞ± NOUN cana-572 165 18 – – PUNCT cana-572 165 19 w*x| w*x| NOUN cana-572 165 20 , , PUNCT cana-572 165 21 dΞ² dΞ² ADJ cana-572 165 22 = = NOUN cana-572 165 23 |c2.xΞ² |c2.xΞ² ADJ cana-572 165 24 – – PUNCT cana-572 165 25 w*x| w*x| NOUN cana-572 165 26 , , PUNCT cana-572 165 27 dΞ΄ dΞ΄ ADP cana-572 165 28 = = PUNCT cana-572 165 29 |c3.xΞ΄ |c3.xΞ΄ PROPN cana-572 165 30 – – PUNCT cana-572 165 31 w*x| w*x| PROPN cana-572 165 32 ( ( PUNCT cana-572 165 33 35 35 NUM cana-572 165 34 ) ) PUNCT cana-572 165 35 particle particle NOUN cana-572 165 36 and and CCONJ cana-572 165 37 wolf wolf PROPN cana-572 165 38 movement movement NOUN cana-572 165 39 : : PUNCT cana-572 165 40 update update VERB cana-572 165 41 the the DET cana-572 165 42 velocity velocity NOUN cana-572 165 43 of of ADP cana-572 165 44 each each DET cana-572 165 45 particle particle NOUN cana-572 165 46 in in ADP cana-572 165 47 pso pso NOUN cana-572 165 48 and and CCONJ cana-572 165 49 the the DET cana-572 165 50 position position NOUN cana-572 165 51 of of ADP cana-572 165 52 each each DET cana-572 165 53 wolf wolf NOUN cana-572 165 54 in in ADP cana-572 165 55 gwo gwo PROPN cana-572 165 56 based base VERB cana-572 165 57 on on ADP cana-572 165 58 their their PRON cana-572 165 59 current current ADJ cana-572 165 60 positions position NOUN cana-572 165 61 and and CCONJ cana-572 165 62 velocities velocity NOUN cana-572 165 63 , , PUNCT cana-572 165 64 similar similar ADJ cana-572 165 65 to to ADP cana-572 165 66 standard standard ADJ cana-572 165 67 pso pso NOUN cana-572 165 68 and and CCONJ cana-572 165 69 gwo gwo PROPN cana-572 165 70 algorithms algorithm NOUN cana-572 165 71 . . PUNCT cana-572 166 1 pso pso NOUN cana-572 166 2 velocity velocity NOUN cana-572 166 3 updates update VERB cana-572 166 4 equation equation NOUN cana-572 166 5 : : PUNCT cana-572 166 6 𝑣𝑖j 𝑣𝑖j ADP cana-572 166 7 𝑑+1 𝑑+1 PROPN cana-572 166 8 = = SYM cana-572 166 9 𝑀(𝑣𝑖j 𝑀(𝑣𝑖j PRON cana-572 166 10 𝑑 𝑑 NOUN cana-572 166 11 + + CCONJ cana-572 166 12 𝑐1 𝑐1 NOUN cana-572 166 13 π‘Ÿ1(𝑋1 π‘Ÿ1(𝑋1 NOUN cana-572 167 1 βˆ’ βˆ’ PUNCT cana-572 167 2 𝑋𝑖 𝑋𝑖 NOUN cana-572 167 3 𝑑 𝑑 PROPN cana-572 167 4 ) ) PUNCT cana-572 167 5 + + NUM cana-572 167 6 𝑐2 𝑐2 NOUN cana-572 168 1 π‘Ÿ2(𝑋2 π‘Ÿ2(𝑋2 NOUN cana-572 168 2 βˆ’ βˆ’ NOUN cana-572 169 1 𝑋𝑖 𝑋𝑖 NOUN cana-572 169 2 𝑑 𝑑 PROPN cana-572 169 3 ) ) PUNCT cana-572 169 4 + + NUM cana-572 169 5 𝑐3 𝑐3 NOUN cana-572 170 1 π‘Ÿ3(𝑋3 π‘Ÿ3(𝑋3 PRON cana-572 170 2 βˆ’ βˆ’ PROPN cana-572 170 3 𝑋𝑖 𝑋𝑖 PROPN cana-572 170 4 𝑑 𝑑 PROPN cana-572 170 5 ) ) PUNCT cana-572 170 6 ) ) PUNCT cana-572 171 1 ( ( PUNCT cana-572 171 2 36 36 NUM cana-572 171 3 ) ) PUNCT cana-572 171 4 then then ADV cana-572 171 5 position position NOUN cana-572 171 6 is be AUX cana-572 171 7 calculated calculate VERB cana-572 171 8 using use VERB cana-572 171 9 updated update VERB cana-572 171 10 velocity velocity NOUN cana-572 171 11 as as ADP cana-572 171 12 in in ADP cana-572 171 13 pso pso NOUN cana-572 171 14 ( ( PUNCT cana-572 171 15 37 37 NUM cana-572 171 16 ) ) PUNCT cana-572 171 17 π‘₯𝑖 π‘₯𝑖 ADP cana-572 171 18 𝑑+1 𝑑+1 PROPN cana-572 171 19 = = SYM cana-572 171 20 π‘₯i π‘₯i NUM cana-572 171 21 𝑑 𝑑 PROPN cana-572 171 22 + + PROPN cana-572 171 23 𝑣𝑖 𝑣𝑖 ADP cana-572 171 24 𝑑+1 𝑑+1 PROPN cana-572 171 25 ( ( PUNCT cana-572 171 26 38 38 NUM cana-572 171 27 ) ) PUNCT cana-572 171 28 fitness fitness NOUN cana-572 171 29 evaluation evaluation NOUN cana-572 171 30 : : PUNCT cana-572 171 31 the the DET cana-572 171 32 goal goal NOUN cana-572 171 33 function function NOUN cana-572 171 34 should should AUX cana-572 171 35 be be AUX cana-572 171 36 used use VERB cana-572 171 37 to to PART cana-572 171 38 determine determine VERB cana-572 171 39 the the DET cana-572 171 40 fitness fitness NOUN cana-572 171 41 of of ADP cana-572 171 42 each each DET cana-572 171 43 wolf wolf NOUN cana-572 171 44 and and CCONJ cana-572 171 45 particle particle PROPN cana-572 171 46 . . PUNCT cana-572 172 1 update update VERB cana-572 172 2 best good ADJ cana-572 172 3 positions position NOUN cana-572 172 4 : : PUNCT cana-572 173 1 update update VERB cana-572 173 2 the the DET cana-572 173 3 personal personal ADJ cana-572 173 4 best good ADJ cana-572 173 5 positions position NOUN cana-572 173 6 ( ( PUNCT cana-572 173 7 pbest pbest NOUN cana-572 173 8 ) ) PUNCT cana-572 173 9 of of ADP cana-572 173 10 particles particle NOUN cana-572 173 11 in in ADP cana-572 173 12 pso pso NOUN cana-572 173 13 and and CCONJ cana-572 173 14 the the DET cana-572 173 15 alpha alpha NOUN cana-572 173 16 , , PUNCT cana-572 173 17 beta beta NOUN cana-572 173 18 , , PUNCT cana-572 173 19 and and CCONJ cana-572 173 20 delta delta NOUN cana-572 173 21 positions position NOUN cana-572 173 22 of of ADP cana-572 173 23 wolves wolf NOUN cana-572 173 24 in in ADP cana-572 173 25 gwo gwo PROPN cana-572 173 26 based base VERB cana-572 173 27 on on ADP cana-572 173 28 the the DET cana-572 173 29 fitness fitness NOUN cana-572 173 30 evaluations evaluation NOUN cana-572 173 31 . . PUNCT cana-572 174 1 hybridization hybridization NOUN cana-572 174 2 : : PUNCT cana-572 174 3 combine combine VERB cana-572 174 4 the the DET cana-572 174 5 movement movement NOUN cana-572 174 6 strategies strategy NOUN cana-572 174 7 of of ADP cana-572 174 8 pso pso NOUN cana-572 174 9 and and CCONJ cana-572 174 10 gwo gwo PROPN cana-572 174 11 , , PUNCT cana-572 174 12 possibly possibly ADV cana-572 174 13 by by ADP cana-572 174 14 assigning assign VERB cana-572 174 15 different different ADJ cana-572 174 16 weights weight NOUN cana-572 174 17 or or CCONJ cana-572 174 18 probabilities probability NOUN cana-572 174 19 to to ADP cana-572 174 20 each each DET cana-572 174 21 algorithm algorithm NOUN cana-572 174 22 's 's PART cana-572 174 23 update update NOUN cana-572 174 24 equations equation NOUN cana-572 174 25 . . PUNCT cana-572 175 1 for for ADP cana-572 175 2 example example NOUN cana-572 175 3 ; ; PUNCT cana-572 175 4 you you PRON cana-572 175 5 could could AUX cana-572 175 6 use use VERB cana-572 175 7 a a DET cana-572 175 8 weighted weighted ADJ cana-572 175 9 average average NOUN cana-572 175 10 of of ADP cana-572 175 11 the the DET cana-572 175 12 velocity velocity NOUN cana-572 175 13 update update NOUN cana-572 175 14 from from ADP cana-572 175 15 pso pso NOUN cana-572 175 16 and and CCONJ cana-572 175 17 the the DET cana-572 175 18 position position NOUN cana-572 175 19 update update NOUN cana-572 175 20 from from ADP cana-572 175 21 gwo gwo PROPN cana-572 175 22 to to PART cana-572 175 23 update update VERB cana-572 175 24 the the DET cana-572 175 25 position position NOUN cana-572 175 26 of of ADP cana-572 175 27 each each DET cana-572 175 28 particle particle NOUN cana-572 175 29 or or CCONJ cana-572 175 30 wolf wolf NOUN cana-572 175 31 . . PUNCT cana-572 176 1 communications communication NOUN cana-572 176 2 on on ADP cana-572 176 3 applied apply VERB cana-572 176 4 nonlinear nonlinear ADJ cana-572 176 5 analysis analysis NOUN cana-572 176 6 issn issn NOUN cana-572 176 7 : : PUNCT cana-572 176 8 1074 1074 NUM cana-572 176 9 - - PUNCT cana-572 176 10 133x 133x NUM cana-572 176 11 vol vol NOUN cana-572 176 12 31 31 NUM cana-572 176 13 no no NOUN cana-572 176 14 . . NOUN cana-572 176 15 2 2 NUM cana-572 176 16 ( ( PUNCT cana-572 176 17 2024 2024 NUM cana-572 176 18 ) ) PUNCT cana-572 176 19 341 341 NUM cana-572 176 20 https://internationalpubls.com https://internationalpubls.com X cana-572 176 21 fig.1 fig.1 PROPN cana-572 176 22 proposed propose VERB cana-572 176 23 flow flow NOUN cana-572 176 24 diagram diagram NOUN cana-572 176 25 termination termination NOUN cana-572 176 26 : : PUNCT cana-572 176 27 iterate iterate VERB cana-572 176 28 through through ADP cana-572 176 29 steps step NOUN cana-572 176 30 3–6 3–6 NUM cana-572 176 31 until until SCONJ cana-572 176 32 a a DET cana-572 176 33 termination termination NOUN cana-572 176 34 condition condition NOUN cana-572 176 35 is be AUX cana-572 176 36 met meet VERB cana-572 176 37 , , PUNCT cana-572 176 38 like like SCONJ cana-572 176 39 as as SCONJ cana-572 176 40 when when SCONJ cana-572 176 41 the the DET cana-572 176 42 maximum maximum ADJ cana-572 176 43 number number NOUN cana-572 176 44 of of ADP cana-572 176 45 iterations iteration NOUN cana-572 176 46 is be AUX cana-572 176 47 reached reach VERB cana-572 176 48 or or CCONJ cana-572 176 49 when when SCONJ cana-572 176 50 a a DET cana-572 176 51 satisfactory satisfactory ADJ cana-572 176 52 solution solution NOUN cana-572 176 53 is be AUX cana-572 176 54 found find VERB cana-572 176 55 . . PUNCT cana-572 177 1 classification classification NOUN cana-572 177 2 : : PUNCT cana-572 177 3 use use VERB cana-572 177 4 the the DET cana-572 177 5 final final ADJ cana-572 177 6 positions position NOUN cana-572 177 7 of of ADP cana-572 177 8 particles particle NOUN cana-572 177 9 or or CCONJ cana-572 177 10 wolves wolf NOUN cana-572 177 11 as as ADP cana-572 177 12 the the DET cana-572 177 13 selected select VERB cana-572 177 14 features feature NOUN cana-572 177 15 for for ADP cana-572 177 16 breast breast NOUN cana-572 177 17 cancer cancer NOUN cana-572 177 18 detection detection NOUN cana-572 177 19 . . PUNCT cana-572 178 1 apply apply VERB cana-572 178 2 a a DET cana-572 178 3 classification classification NOUN cana-572 178 4 algorithm algorithm NOUN cana-572 178 5 like like ADP cana-572 178 6 svm svm PROPN cana-572 178 7 , , PUNCT cana-572 178 8 knn knn PROPN cana-572 178 9 , , PUNCT cana-572 178 10 lr lr NOUN cana-572 178 11 , , PUNCT cana-572 178 12 and and CCONJ cana-572 178 13 random random ADJ cana-572 178 14 forest forest NOUN cana-572 178 15 rf rf VERB cana-572 178 16 to to PART cana-572 178 17 classify classify VERB cana-572 178 18 the the DET cana-572 178 19 breast breast NOUN cana-572 178 20 cancer cancer NOUN cana-572 178 21 instances instance NOUN cana-572 178 22 based base VERB cana-572 178 23 on on ADP cana-572 178 24 the the DET cana-572 178 25 selected select VERB cana-572 178 26 features feature NOUN cana-572 178 27 . . PUNCT cana-572 179 1 4 4 X cana-572 179 2 . . X cana-572 179 3 experiment experiment NOUN cana-572 179 4 setup setup NOUN cana-572 179 5 and and CCONJ cana-572 179 6 proposed propose VERB cana-572 179 7 system system NOUN cana-572 179 8 during during ADP cana-572 179 9 the the DET cana-572 179 10 course course NOUN cana-572 179 11 of of ADP cana-572 179 12 this this DET cana-572 179 13 research research NOUN cana-572 179 14 endeavor endeavor NOUN cana-572 179 15 , , PUNCT cana-572 179 16 the the DET cana-572 179 17 breast breast NOUN cana-572 179 18 cancer cancer NOUN cana-572 179 19 dataset dataset NOUN cana-572 179 20 , , PUNCT cana-572 179 21 which which PRON cana-572 179 22 was be AUX cana-572 179 23 obtained obtain VERB cana-572 179 24 from from ADP cana-572 179 25 the the DET cana-572 179 26 uci uci PROPN cana-572 179 27 machine machine NOUN cana-572 179 28 learning learn VERB cana-572 179 29 repository repository NOUN cana-572 179 30 , , PUNCT cana-572 179 31 was be AUX cana-572 179 32 utilized.the utilized.the DET cana-572 179 33 dataset dataset NOUN cana-572 179 34 was be AUX cana-572 179 35 then then ADV cana-572 179 36 subjected subject VERB cana-572 179 37 to to ADP cana-572 179 38 pre pre ADJ cana-572 179 39 - - ADJ cana-572 179 40 processing processing ADJ cana-572 179 41 procedures procedure NOUN cana-572 179 42 in in ADP cana-572 179 43 order order NOUN cana-572 179 44 to to PART cana-572 179 45 get get VERB cana-572 179 46 it it PRON cana-572 179 47 ready ready ADJ cana-572 179 48 for for ADP cana-572 179 49 analysis analysis NOUN cana-572 179 50 , , PUNCT cana-572 179 51 which which PRON cana-572 179 52 included include VERB cana-572 179 53 dealing deal VERB cana-572 179 54 with with ADP cana-572 179 55 any any DET cana-572 179 56 missing miss VERB cana-572 179 57 variables variable NOUN cana-572 179 58 . . PUNCT cana-572 180 1 following follow VERB cana-572 180 2 preprocessing preprocesse VERB cana-572 180 3 , , PUNCT cana-572 180 4 we we PRON cana-572 180 5 separated separate VERB cana-572 180 6 the the DET cana-572 180 7 dataset dataset NOUN cana-572 180 8 into into ADP cana-572 180 9 training training NOUN cana-572 180 10 and and CCONJ cana-572 180 11 testing testing NOUN cana-572 180 12 sets set NOUN cana-572 180 13 , , PUNCT cana-572 180 14 which which PRON cana-572 180 15 were be AUX cana-572 180 16 used use VERB cana-572 180 17 for for ADP cana-572 180 18 the the DET cana-572 180 19 construction construction NOUN cana-572 180 20 of of ADP cana-572 180 21 the the DET cana-572 180 22 model model NOUN cana-572 180 23 and and CCONJ cana-572 180 24 the the DET cana-572 180 25 evaluation evaluation NOUN cana-572 180 26 of of ADP cana-572 180 27 the the DET cana-572 180 28 model model NOUN cana-572 180 29 , , PUNCT cana-572 180 30 respectively respectively ADV cana-572 180 31 . . PUNCT cana-572 181 1 for for ADP cana-572 181 2 optimization optimization NOUN cana-572 181 3 algorithms algorithm NOUN cana-572 181 4 such such ADJ cana-572 181 5 as as ADP cana-572 181 6 pso pso NOUN cana-572 181 7 , , PUNCT cana-572 181 8 gwo gwo PROPN cana-572 181 9 , , PUNCT cana-572 181 10 and and CCONJ cana-572 181 11 a a DET cana-572 181 12 hybrid hybrid ADJ cana-572 181 13 approach approach NOUN cana-572 181 14 combining combine VERB cana-572 181 15 pso pso NOUN cana-572 181 16 with with ADP cana-572 181 17 gwo gwo PROPN cana-572 181 18 . . PUNCT cana-572 182 1 these these DET cana-572 182 2 algorithms algorithm NOUN cana-572 182 3 were be AUX cana-572 182 4 used use VERB cana-572 182 5 to to PART cana-572 182 6 identify identify VERB cana-572 182 7 the the DET cana-572 182 8 most most ADV cana-572 182 9 relevant relevant ADJ cana-572 182 10 features feature NOUN cana-572 182 11 from from ADP cana-572 182 12 the the DET cana-572 182 13 dataset dataset NOUN cana-572 182 14 , , PUNCT cana-572 182 15 thereby thereby ADV cana-572 182 16 improving improve VERB cana-572 182 17 the the DET cana-572 182 18 efficiency efficiency NOUN cana-572 182 19 and and CCONJ cana-572 182 20 effectiveness effectiveness NOUN cana-572 182 21 of of ADP cana-572 182 22 our our PRON cana-572 182 23 models model NOUN cana-572 182 24 . . PUNCT cana-572 183 1 the the DET cana-572 183 2 results result NOUN cana-572 183 3 of of ADP cana-572 183 4 our our PRON cana-572 183 5 study study NOUN cana-572 183 6 demonstrated demonstrate VERB cana-572 183 7 the the DET cana-572 183 8 effectiveness effectiveness NOUN cana-572 183 9 of of ADP cana-572 183 10 different different ADJ cana-572 183 11 feature feature NOUN cana-572 183 12 selection selection NOUN cana-572 183 13 and and CCONJ cana-572 183 14 classifier classifier NOUN cana-572 183 15 combinations combination NOUN cana-572 183 16 in in ADP cana-572 183 17 predicting predict VERB cana-572 183 18 breast breast NOUN cana-572 183 19 cancer cancer NOUN cana-572 183 20 outcomes outcome NOUN cana-572 183 21 . . PUNCT cana-572 184 1 by by ADP cana-572 184 2 comparing compare VERB cana-572 184 3 the the DET cana-572 184 4 performance performance NOUN cana-572 184 5 metrics metric NOUN cana-572 184 6 of of ADP cana-572 184 7 each each DET cana-572 184 8 model model NOUN cana-572 184 9 , , PUNCT cana-572 184 10 we we PRON cana-572 184 11 were be AUX cana-572 184 12 able able ADJ cana-572 184 13 to to PART cana-572 184 14 identify identify VERB cana-572 184 15 the the DET cana-572 184 16 most most ADV cana-572 184 17 accurate accurate ADJ cana-572 184 18 and and CCONJ cana-572 184 19 reliable reliable ADJ cana-572 184 20 classifiers classifier NOUN cana-572 184 21 for for ADP cana-572 184 22 breast breast NOUN cana-572 184 23 cancer cancer NOUN cana-572 184 24 prediction prediction NOUN cana-572 184 25 . . PUNCT cana-572 185 1 5 5 X cana-572 185 2 . . X cana-572 185 3 result result NOUN cana-572 185 4 & & CCONJ cana-572 185 5 discussion discussion NOUN cana-572 185 6 this this DET cana-572 185 7 section section NOUN cana-572 185 8 discusses discuss VERB cana-572 185 9 ml ml ADP cana-572 185 10 classification classification NOUN cana-572 185 11 models model NOUN cana-572 185 12 and and CCONJ cana-572 185 13 outcomes outcome NOUN cana-572 185 14 from from ADP cana-572 185 15 diverse diverse ADJ cana-572 185 16 methodologies methodology NOUN cana-572 185 17 . . PUNCT cana-572 186 1 initially initially ADV cana-572 186 2 , , PUNCT cana-572 186 3 we we PRON cana-572 186 4 used use VERB cana-572 186 5 ml ml ADP cana-572 186 6 classifiers classifier NOUN cana-572 186 7 to to PART cana-572 186 8 eliminate eliminate VERB cana-572 186 9 missing missing ADJ cana-572 186 10 values value NOUN cana-572 186 11 and and CCONJ cana-572 186 12 undesirable undesirable ADJ cana-572 186 13 data datum NOUN cana-572 186 14 from from ADP cana-572 186 15 preprocessed preprocesse VERB cana-572 186 16 data datum NOUN cana-572 186 17 . . PUNCT cana-572 187 1 during during ADP cana-572 187 2 the the DET cana-572 187 3 second second ADJ cana-572 187 4 stage stage NOUN cana-572 187 5 , , PUNCT cana-572 187 6 we we PRON cana-572 187 7 used use VERB cana-572 187 8 pso pso NOUN cana-572 187 9 , , PUNCT cana-572 187 10 gwo gwo PROPN cana-572 187 11 , , PUNCT cana-572 187 12 and and CCONJ cana-572 187 13 a a DET cana-572 187 14 hybrid hybrid ADJ cana-572 187 15 strategy strategy NOUN cana-572 187 16 , , PUNCT cana-572 187 17 as as ADV cana-572 187 18 well well ADV cana-572 187 19 as as ADP cana-572 187 20 wrapper wrapper NOUN cana-572 187 21 approaches approach NOUN cana-572 187 22 including include VERB cana-572 187 23 svm svm PROPN cana-572 187 24 , , PUNCT cana-572 187 25 knn knn PROPN cana-572 187 26 , , PUNCT cana-572 187 27 lr lr NOUN cana-572 187 28 , , PUNCT cana-572 187 29 and and CCONJ cana-572 187 30 rf rf PROPN cana-572 187 31 , , PUNCT cana-572 187 32 ann ann PROPN cana-572 187 33 , , PUNCT cana-572 187 34 on on ADP cana-572 187 35 both both CCONJ cana-572 187 36 preprocessed preprocesse VERB cana-572 187 37 and and CCONJ cana-572 187 38 unprocessed unprocessed ADJ cana-572 187 39 datasets dataset NOUN cana-572 187 40 . . PUNCT cana-572 188 1 the the DET cana-572 188 2 total total ADJ cana-572 188 3 number number NOUN cana-572 188 4 of of ADP cana-572 188 5 characteristics characteristic NOUN cana-572 188 6 that that PRON cana-572 188 7 were be AUX cana-572 188 8 chosen choose VERB cana-572 188 9 using use VERB cana-572 188 10 these these DET cana-572 188 11 methods method NOUN cana-572 188 12 . . PUNCT cana-572 189 1 the the DET cana-572 189 2 comparison comparison NOUN cana-572 189 3 of of ADP cana-572 189 4 the the DET cana-572 189 5 accuracy accuracy NOUN cana-572 189 6 of of ADP cana-572 189 7 these these DET cana-572 189 8 classifiers classifier NOUN cana-572 189 9 with with ADP cana-572 189 10 the the DET cana-572 189 11 accuracy accuracy NOUN cana-572 189 12 ( ( PUNCT cana-572 189 13 percentage percentage NOUN cana-572 189 14 ) ) PUNCT cana-572 189 15 results result NOUN cana-572 189 16 of of ADP cana-572 189 17 virtual virtual ADJ cana-572 189 18 machine machine NOUN cana-572 189 19 models model NOUN cana-572 189 20 that that PRON cana-572 189 21 were be AUX cana-572 189 22 trained train VERB cana-572 189 23 with with ADP cana-572 189 24 a a DET cana-572 189 25 variety variety NOUN cana-572 189 26 of of ADP cana-572 189 27 data datum NOUN cana-572 189 28 splitting splitting NOUN cana-572 189 29 ratios ratio NOUN cana-572 189 30 ( ( PUNCT cana-572 189 31 9010 9010 NUM cana-572 189 32 , , PUNCT cana-572 189 33 80 80 NUM cana-572 189 34 - - SYM cana-572 189 35 20 20 NUM cana-572 189 36 , , PUNCT cana-572 189 37 70 70 NUM cana-572 189 38 - - SYM cana-572 189 39 30 30 NUM cana-572 189 40 , , PUNCT cana-572 189 41 and and CCONJ cana-572 189 42 60 60 NUM cana-572 189 43 - - SYM cana-572 189 44 40 40 NUM cana-572 189 45 ) ) PUNCT cana-572 189 46 and and CCONJ cana-572 189 47 optimized optimize VERB cana-572 189 48 with with ADP cana-572 189 49 a a DET cana-572 189 50 number number NOUN cana-572 189 51 of of ADP cana-572 189 52 different different ADJ cana-572 189 53 optimization optimization NOUN cana-572 189 54 algorithms algorithms NOUN cana-572 189 55 communications communication NOUN cana-572 189 56 on on ADP cana-572 189 57 applied apply VERB cana-572 189 58 nonlinear nonlinear ADJ cana-572 189 59 analysis analysis NOUN cana-572 189 60 issn issn NOUN cana-572 189 61 : : PUNCT cana-572 189 62 1074 1074 NUM cana-572 189 63 - - PUNCT cana-572 189 64 133x 133x NUM cana-572 189 65 vol vol NOUN cana-572 189 66 31 31 NUM cana-572 189 67 no no NOUN cana-572 189 68 . . NOUN cana-572 189 69 2 2 NUM cana-572 189 70 ( ( PUNCT cana-572 189 71 2024 2024 NUM cana-572 189 72 ) ) PUNCT cana-572 189 73 342 342 NUM cana-572 189 74 https://internationalpubls.com https://internationalpubls.com X cana-572 189 75 performance performance NOUN cana-572 189 76 evaluation evaluation NOUN cana-572 189 77 metrics metric NOUN cana-572 189 78 performance performance NOUN cana-572 189 79 evaluation evaluation NOUN cana-572 189 80 metrics metric NOUN cana-572 189 81 are be AUX cana-572 189 82 crucial crucial ADJ cana-572 189 83 for for ADP cana-572 189 84 assessing assess VERB cana-572 189 85 the the DET cana-572 189 86 effectiveness effectiveness NOUN cana-572 189 87 of of ADP cana-572 189 88 machine machine NOUN cana-572 189 89 learning learn VERB cana-572 189 90 classifiers classifier NOUN cana-572 189 91 . . PUNCT cana-572 190 1 the the DET cana-572 190 2 commonly commonly ADV cana-572 190 3 used use VERB cana-572 190 4 metrics metric NOUN cana-572 190 5 include include VERB cana-572 190 6 classification classification NOUN cana-572 190 7 accuracy accuracy NOUN cana-572 190 8 , , PUNCT cana-572 190 9 precision precision NOUN cana-572 190 10 , , PUNCT cana-572 190 11 recall recall NOUN cana-572 190 12 table table NOUN cana-572 190 13 1 1 NUM cana-572 190 14 performance performance NOUN cana-572 190 15 of of ADP cana-572 190 16 different different ADJ cana-572 190 17 feature feature NOUN cana-572 190 18 selection selection NOUN cana-572 190 19 and and CCONJ cana-572 190 20 classification classification NOUN cana-572 190 21 techniques technique NOUN cana-572 190 22 train train NOUN cana-572 190 23 test test NOUN cana-572 190 24 ratio ratio NOUN cana-572 190 25 all all PRON cana-572 190 26 features feature VERB cana-572 190 27 pso pso PROPN cana-572 190 28 gwo gwo PROPN cana-572 190 29 hpsogwo hpsogwo PROPN cana-572 190 30 accuracy accuracy PROPN cana-572 190 31 precision precision PROPN cana-572 190 32 recall recall PROPN cana-572 190 33 accuracy accuracy PROPN cana-572 190 34 precision precision NOUN cana-572 190 35 recall recall PROPN cana-572 190 36 accuracy accuracy PROPN cana-572 190 37 precision precision NOUN cana-572 190 38 recall recall PROPN cana-572 190 39 accuracy accuracy PROPN cana-572 190 40 precision precision NOUN cana-572 190 41 recall recall NOUN cana-572 190 42 svm svm VERB cana-572 190 43 90 90 NUM cana-572 190 44 - - SYM cana-572 190 45 10 10 NUM cana-572 190 46 96.49 96.49 NUM cana-572 190 47 97.22 97.22 NUM cana-572 190 48 97.22 97.22 NUM cana-572 190 49 92.98 92.98 NUM cana-572 190 50 97.06 97.06 NUM cana-572 190 51 91.67 91.67 NUM cana-572 190 52 96.49 96.49 NUM cana-572 190 53 97.22 97.22 NUM cana-572 190 54 97.22 97.22 NUM cana-572 190 55 92.08 92.08 NUM cana-572 190 56 97.06 97.06 NUM cana-572 190 57 91.67 91.67 NUM cana-572 190 58 80 80 NUM cana-572 190 59 - - SYM cana-572 190 60 20 20 NUM cana-572 190 61 98.25 98.25 NUM cana-572 190 62 98.60 98.60 NUM cana-572 190 63 98.60 98.60 NUM cana-572 190 64 95.61 95.61 NUM cana-572 190 65 97.18 97.18 NUM cana-572 190 66 95.83 95.83 NUM cana-572 190 67 97.37 97.37 NUM cana-572 190 68 97.26 97.26 NUM cana-572 190 69 98.60 98.60 NUM cana-572 190 70 95.61 95.61 NUM cana-572 190 71 97.18 97.18 NUM cana-572 190 72 95.83 95.83 NUM cana-572 190 73 70 70 NUM cana-572 190 74 - - SYM cana-572 190 75 30 30 NUM cana-572 190 76 97.66 97.66 NUM cana-572 190 77 98.13 98.13 NUM cana-572 190 78 98.30 98.30 NUM cana-572 190 79 97.49 97.49 NUM cana-572 190 80 98.13 98.13 NUM cana-572 190 81 97.20 97.20 NUM cana-572 190 82 97.66 97.66 NUM cana-572 190 83 97.20 97.20 NUM cana-572 190 84 99.07 99.07 NUM cana-572 190 85 97.08 97.08 NUM cana-572 190 86 97.22 97.22 NUM cana-572 190 87 98.13 98.13 NUM cana-572 190 88 60 60 NUM cana-572 190 89 - - SYM cana-572 190 90 40 40 NUM cana-572 190 91 96.93 96.93 NUM cana-572 190 92 96.58 96.58 NUM cana-572 190 93 98.60 98.60 NUM cana-572 190 94 97.81 97.81 NUM cana-572 190 95 97.92 97.92 NUM cana-572 190 96 98.60 98.60 NUM cana-572 190 97 97.81 97.81 NUM cana-572 190 98 97.26 97.26 NUM cana-572 190 99 99.30 99.30 NUM cana-572 190 100 98.25 98.25 NUM cana-572 190 101 97.28 97.28 NUM cana-572 190 102 100.00 100.00 NUM cana-572 190 103 knn knn NOUN cana-572 190 104 90 90 NUM cana-572 190 105 - - SYM cana-572 190 106 10 10 NUM cana-572 190 107 98.25 98.25 NUM cana-572 190 108 97.30 97.30 NUM cana-572 190 109 99.00 99.00 NUM cana-572 190 110 96.49 96.49 NUM cana-572 190 111 97.22 97.22 NUM cana-572 190 112 97.22 97.22 NUM cana-572 190 113 98.25 98.25 NUM cana-572 190 114 97.30 97.30 NUM cana-572 190 115 100.00 100.00 NUM cana-572 190 116 94.74 94.74 NUM cana-572 190 117 97.14 97.14 NUM cana-572 190 118 94.44 94.44 NUM cana-572 190 119 80 80 NUM cana-572 190 120 - - SYM cana-572 190 121 20 20 NUM cana-572 190 122 98.25 98.25 NUM cana-572 190 123 97.30 97.30 NUM cana-572 190 124 98.00 98.00 NUM cana-572 190 125 93.86 93.86 NUM cana-572 190 126 97.10 97.10 NUM cana-572 190 127 93.06 93.06 NUM cana-572 190 128 93.86 93.86 NUM cana-572 190 129 95.77 95.77 NUM cana-572 190 130 94.44 94.44 NUM cana-572 190 131 93.86 93.86 NUM cana-572 190 132 97.10 97.10 NUM cana-572 190 133 93.06 93.06 NUM cana-572 190 134 70 70 NUM cana-572 190 135 - - SYM cana-572 190 136 30 30 NUM cana-572 190 137 97.60 97.60 NUM cana-572 190 138 96.40 96.40 NUM cana-572 190 139 98.00 98.00 NUM cana-572 190 140 94.74 94.74 NUM cana-572 190 141 95.37 95.37 NUM cana-572 190 142 96.26 96.26 NUM cana-572 190 143 95.32 95.32 NUM cana-572 190 144 94.59 94.59 NUM cana-572 190 145 98.13 98.13 NUM cana-572 190 146 95.32 95.32 NUM cana-572 190 147 95.41 95.41 NUM cana-572 190 148 97.20 97.20 NUM cana-572 190 149 60 60 NUM cana-572 190 150 - - SYM cana-572 190 151 40 40 NUM cana-572 190 152 96.05 96.05 NUM cana-572 190 153 95.89 95.89 NUM cana-572 190 154 97.90 97.90 NUM cana-572 190 155 95.18 95.18 NUM cana-572 190 156 95.21 95.21 NUM cana-572 190 157 97.20 97.20 NUM cana-572 190 158 95.18 95.18 NUM cana-572 190 159 94.59 94.59 NUM cana-572 190 160 97.90 97.90 NUM cana-572 190 161 96.49 96.49 NUM cana-572 190 162 96.55 96.55 NUM cana-572 190 163 97.90 97.90 NUM cana-572 190 164 lr lr INTJ cana-572 190 165 90 90 NUM cana-572 190 166 - - SYM cana-572 190 167 10 10 NUM cana-572 190 168 96.49 96.49 NUM cana-572 190 169 97.22 97.22 NUM cana-572 190 170 97.22 97.22 NUM cana-572 190 171 98.25 98.25 NUM cana-572 190 172 97.30 97.30 NUM cana-572 190 173 99.00 99.00 NUM cana-572 190 174 92.98 92.98 NUM cana-572 190 175 97.06 97.06 NUM cana-572 190 176 91.67 91.67 NUM cana-572 190 177 96.49 96.49 NUM cana-572 190 178 97.22 97.22 NUM cana-572 190 179 97.22 97.22 NUM cana-572 190 180 80 80 NUM cana-572 190 181 - - SYM cana-572 190 182 20 20 NUM cana-572 190 183 95.01 95.01 NUM cana-572 190 184 94.67 94.67 NUM cana-572 190 185 98.61 98.61 NUM cana-572 190 186 96.49 96.49 NUM cana-572 190 187 95.95 95.95 NUM cana-572 190 188 98.61 98.61 NUM cana-572 190 189 94.74 94.74 NUM cana-572 190 190 95.83 95.83 NUM cana-572 190 191 95.83 95.83 NUM cana-572 190 192 93.86 93.86 NUM cana-572 190 193 93.33 93.33 NUM cana-572 190 194 97.22 97.22 NUM cana-572 190 195 70 70 NUM cana-572 190 196 - - SYM cana-572 190 197 30 30 NUM cana-572 190 198 94.74 94.74 NUM cana-572 190 199 92.98 92.98 NUM cana-572 190 200 99.07 99.07 NUM cana-572 190 201 94.74 94.74 NUM cana-572 190 202 92.24 92.24 NUM cana-572 190 203 99.00 99.00 NUM cana-572 190 204 94.50 94.50 NUM cana-572 190 205 92.92 92.92 NUM cana-572 190 206 98.13 98.13 NUM cana-572 190 207 93.57 93.57 NUM cana-572 190 208 92.11 92.11 NUM cana-572 190 209 98.13 98.13 NUM cana-572 190 210 60 60 NUM cana-572 190 211 - - SYM cana-572 190 212 40 40 NUM cana-572 190 213 95.80 95.80 NUM cana-572 190 214 94.00 94.00 NUM cana-572 190 215 98.60 98.60 NUM cana-572 190 216 95.61 95.61 NUM cana-572 190 217 94.04 94.04 NUM cana-572 190 218 99.30 99.30 NUM cana-572 190 219 95.61 95.61 NUM cana-572 190 220 94.63 94.63 NUM cana-572 190 221 98.63 98.63 NUM cana-572 190 222 94.74 94.74 NUM cana-572 190 223 93.38 93.38 NUM cana-572 190 224 98.60 98.60 NUM cana-572 190 225 rf rf NUM cana-572 190 226 90 90 NUM cana-572 190 227 - - SYM cana-572 190 228 10 10 NUM cana-572 190 229 96.49 96.49 NUM cana-572 190 230 97.22 97.22 NUM cana-572 190 231 97.22 97.22 NUM cana-572 190 232 94.74 94.74 NUM cana-572 190 233 97.14 97.14 NUM cana-572 190 234 94.44 94.44 NUM cana-572 190 235 92.98 92.98 NUM cana-572 190 236 97.06 97.06 NUM cana-572 190 237 91.67 91.67 NUM cana-572 190 238 94.74 94.74 NUM cana-572 190 239 97.14 97.14 NUM cana-572 190 240 94.44 94.44 NUM cana-572 190 241 80 80 NUM cana-572 190 242 - - SYM cana-572 190 243 20 20 NUM cana-572 190 244 94.74 94.74 NUM cana-572 190 245 95.83 95.83 NUM cana-572 190 246 95.83 95.83 NUM cana-572 190 247 95.61 95.61 NUM cana-572 190 248 97.18 97.18 NUM cana-572 190 249 95.83 95.83 NUM cana-572 190 250 96.49 96.49 NUM cana-572 190 251 95.95 95.95 NUM cana-572 190 252 98.60 98.60 NUM cana-572 190 253 94.74 94.74 NUM cana-572 190 254 95.83 95.83 NUM cana-572 190 255 95.83 95.83 NUM cana-572 190 256 70 70 NUM cana-572 190 257 - - SYM cana-572 190 258 30 30 NUM cana-572 190 259 95.32 95.32 NUM cana-572 190 260 95.41 95.41 NUM cana-572 190 261 97.20 97.20 NUM cana-572 190 262 95.32 95.32 NUM cana-572 190 263 95.14 95.14 NUM cana-572 190 264 97.20 97.20 NUM cana-572 190 265 94.15 94.15 NUM cana-572 190 266 95.33 95.33 NUM cana-572 190 267 95.33 95.33 NUM cana-572 190 268 94.15 94.15 NUM cana-572 190 269 94.50 94.50 NUM cana-572 190 270 96.26 96.26 NUM cana-572 190 271 60 60 NUM cana-572 190 272 - - SYM cana-572 190 273 40 40 NUM cana-572 190 274 94.74 94.74 NUM cana-572 190 275 95.17 95.17 NUM cana-572 190 276 96.50 96.50 NUM cana-572 190 277 96.49 96.49 NUM cana-572 190 278 96.55 96.55 NUM cana-572 190 279 97.90 97.90 NUM cana-572 190 280 95.18 95.18 NUM cana-572 190 281 95.83 95.83 NUM cana-572 190 282 96.50 96.50 NUM cana-572 190 283 93.86 93.86 NUM cana-572 190 284 94.48 94.48 NUM cana-572 190 285 95.80 95.80 NUM cana-572 190 286 ann ann PROPN cana-572 190 287 90 90 NUM cana-572 190 288 - - SYM cana-572 190 289 10 10 NUM cana-572 190 290 96.49 96.49 NUM cana-572 190 291 97.22 97.22 NUM cana-572 190 292 97.22 97.22 NUM cana-572 190 293 92.98 92.98 NUM cana-572 190 294 97.06 97.06 NUM cana-572 190 295 91.67 91.67 NUM cana-572 190 296 91.23 91.23 NUM cana-572 190 297 96.97 96.97 NUM cana-572 190 298 98.89 98.89 NUM cana-572 190 299 94.74 94.74 NUM cana-572 190 300 97.14 97.14 NUM cana-572 190 301 94.44 94.44 NUM cana-572 190 302 80 80 NUM cana-572 190 303 - - SYM cana-572 190 304 20 20 NUM cana-572 190 305 97.37 97.37 NUM cana-572 190 306 98.59 98.59 NUM cana-572 190 307 97.22 97.22 NUM cana-572 190 308 95.61 95.61 NUM cana-572 190 309 97.18 97.18 NUM cana-572 190 310 95.83 95.83 NUM cana-572 190 311 94.74 94.74 NUM cana-572 190 312 95.83 95.83 NUM cana-572 190 313 95.83 95.83 NUM cana-572 190 314 96.49 96.49 NUM cana-572 190 315 98.57 98.57 NUM cana-572 190 316 95.83 95.83 NUM cana-572 190 317 70 70 NUM cana-572 190 318 - - SYM cana-572 190 319 30 30 NUM cana-572 190 320 98.25 98.25 NUM cana-572 190 321 99.06 99.06 NUM cana-572 190 322 98.30 98.30 NUM cana-572 190 323 95.91 95.91 NUM cana-572 190 324 96.30 96.30 NUM cana-572 190 325 97.20 97.20 NUM cana-572 190 326 95.32 95.32 NUM cana-572 190 327 95.41 95.41 NUM cana-572 190 328 97.20 97.20 NUM cana-572 190 329 97.08 97.08 NUM cana-572 190 330 98.11 98.11 NUM cana-572 190 331 97.20 97.20 NUM cana-572 190 332 60 60 NUM cana-572 190 333 - - SYM cana-572 190 334 40 40 NUM cana-572 190 335 98.68 98.68 NUM cana-572 190 336 99.30 99.30 NUM cana-572 190 337 98.60 98.60 NUM cana-572 190 338 96.61 96.61 NUM cana-572 190 339 96.50 96.50 NUM cana-572 190 340 96.50 96.50 NUM cana-572 190 341 95.60 95.60 NUM cana-572 190 342 95.85 95.85 NUM cana-572 190 343 97.20 97.20 NUM cana-572 190 344 96.93 96.93 NUM cana-572 190 345 97.89 97.89 NUM cana-572 190 346 97.20 97.20 NUM cana-572 190 347 classification classification NOUN cana-572 190 348 accuracy accuracy NOUN cana-572 190 349 : : PUNCT cana-572 190 350 the the DET cana-572 190 351 accuracy accuracy NOUN cana-572 190 352 of of ADP cana-572 190 353 classification classification NOUN cana-572 190 354 is be AUX cana-572 190 355 determined determine VERB cana-572 190 356 by by ADP cana-572 190 357 determining determine VERB cana-572 190 358 the the DET cana-572 190 359 percentage percentage NOUN cana-572 190 360 of of ADP cana-572 190 361 data datum NOUN cana-572 190 362 points point NOUN cana-572 190 363 that that PRON cana-572 190 364 have have AUX cana-572 190 365 been be AUX cana-572 190 366 successfully successfully ADV cana-572 190 367 classified classify VERB cana-572 190 368 out out ADP cana-572 190 369 of of ADP cana-572 190 370 the the DET cana-572 190 371 total total ADJ cana-572 190 372 number number NOUN cana-572 190 373 of of ADP cana-572 190 374 data datum NOUN cana-572 190 375 points point NOUN cana-572 190 376 . . PUNCT cana-572 191 1 calculated calculate VERB cana-572 191 2 by by ADP cana-572 191 3 taking take VERB cana-572 191 4 the the DET cana-572 191 5 total total ADJ cana-572 191 6 number number NOUN cana-572 191 7 of of ADP cana-572 191 8 data datum NOUN cana-572 191 9 points point NOUN cana-572 191 10 and and CCONJ cana-572 191 11 dividing divide VERB cana-572 191 12 it it PRON cana-572 191 13 by by ADP cana-572 191 14 the the DET cana-572 191 15 sum sum NOUN cana-572 191 16 of of ADP cana-572 191 17 true true ADJ cana-572 191 18 positives positive NOUN cana-572 191 19 ( ( PUNCT cana-572 191 20 tp tp NOUN cana-572 191 21 ) ) PUNCT cana-572 191 22 and and CCONJ cana-572 191 23 true true ADJ cana-572 191 24 negatives negative NOUN cana-572 191 25 ( ( PUNCT cana-572 191 26 tn tn NOUN cana-572 191 27 ) ) PUNCT cana-572 191 28 , , PUNCT cana-572 191 29 it it PRON cana-572 191 30 includes include VERB cana-572 191 31 the the DET cana-572 191 32 following following NOUN cana-572 191 33 : : PUNCT cana-572 191 34 accuracy= accuracy= NUM cana-572 191 35 𝐓𝐏+𝐓𝐍+𝐅𝐏+𝐅𝐍 𝐓𝐏+𝐓𝐍+𝐅𝐏+𝐅𝐍 PROPN cana-572 191 36 𝐓𝐏+𝐓𝐍 𝐓𝐏+𝐓𝐍 ADJ cana-572 191 37 precision precision NOUN cana-572 191 38 : : PUNCT cana-572 191 39 accuracy accuracy NOUN cana-572 191 40 can can AUX cana-572 191 41 be be AUX cana-572 191 42 defined define VERB cana-572 191 43 as as ADP cana-572 191 44 the the DET cana-572 191 45 ratio ratio NOUN cana-572 191 46 of of ADP cana-572 191 47 the the DET cana-572 191 48 actual actual ADJ cana-572 191 49 positive positive ADJ cana-572 191 50 to to ADP cana-572 191 51 the the DET cana-572 191 52 total total ADJ cana-572 191 53 number number NOUN cana-572 191 54 of of ADP cana-572 191 55 positives positive NOUN cana-572 191 56 anticipated anticipate VERB cana-572 191 57 . . PUNCT cana-572 192 1 a a DET cana-572 192 2 model model NOUN cana-572 192 3 with with ADP cana-572 192 4 a a DET cana-572 192 5 high high ADJ cana-572 192 6 precision precision NOUN cana-572 192 7 has have VERB cana-572 192 8 a a DET cana-572 192 9 low low ADJ cana-572 192 10 false false ADJ cana-572 192 11 positive positive ADJ cana-572 192 12 rate rate NOUN cana-572 192 13 , , PUNCT cana-572 192 14 which which PRON cana-572 192 15 means mean VERB cana-572 192 16 that that SCONJ cana-572 192 17 it it PRON cana-572 192 18 only only ADV cana-572 192 19 sometimes sometimes ADV cana-572 192 20 incorrectly incorrectly ADV cana-572 192 21 identifies identify VERB cana-572 192 22 negative negative ADJ cana-572 192 23 occurrences occurrence NOUN cana-572 192 24 as as ADP cana-572 192 25 positive positive ADJ cana-572 192 26 . . PUNCT cana-572 193 1 conversely conversely ADV cana-572 193 2 , , PUNCT cana-572 193 3 a a DET cana-572 193 4 low low ADJ cana-572 193 5 precision precision NOUN cana-572 193 6 suggests suggest VERB cana-572 193 7 that that SCONJ cana-572 193 8 the the DET cana-572 193 9 model model NOUN cana-572 193 10 tends tend VERB cana-572 193 11 to to PART cana-572 193 12 make make VERB cana-572 193 13 a a DET cana-572 193 14 significant significant ADJ cana-572 193 15 number number NOUN cana-572 193 16 of of ADP cana-572 193 17 false false ADJ cana-572 193 18 positive positive ADJ cana-572 193 19 communications communication NOUN cana-572 193 20 on on ADP cana-572 193 21 applied apply VERB cana-572 193 22 nonlinear nonlinear ADJ cana-572 193 23 analysis analysis NOUN cana-572 193 24 issn issn NOUN cana-572 193 25 : : PUNCT cana-572 193 26 1074 1074 NUM cana-572 193 27 - - PUNCT cana-572 193 28 133x 133x NUM cana-572 193 29 vol vol NOUN cana-572 193 30 31 31 NUM cana-572 193 31 no no NOUN cana-572 193 32 . . NOUN cana-572 193 33 2 2 NUM cana-572 193 34 ( ( PUNCT cana-572 193 35 2024 2024 NUM cana-572 193 36 ) ) PUNCT cana-572 193 37 343 343 NUM cana-572 193 38 https://internationalpubls.com https://internationalpubls.com X cana-572 193 39 predictions prediction NOUN cana-572 193 40 , , PUNCT cana-572 193 41 which which PRON cana-572 193 42 can can AUX cana-572 193 43 be be AUX cana-572 193 44 problematic problematic ADJ cana-572 193 45 in in ADP cana-572 193 46 scenarios scenario NOUN cana-572 193 47 where where SCONJ cana-572 193 48 false false ADJ cana-572 193 49 positives positive NOUN cana-572 193 50 are be AUX cana-572 193 51 costly costly ADJ cana-572 193 52 or or CCONJ cana-572 193 53 undesirable undesirable ADJ cana-572 193 54 as as ADP cana-572 193 55 in in ADP cana-572 193 56 fraud fraud NOUN cana-572 193 57 detection detection NOUN cana-572 193 58 , , PUNCT cana-572 193 59 and and CCONJ cana-572 193 60 spam spam NOUN cana-572 193 61 filtering filtering NOUN cana-572 193 62 . . PUNCT cana-572 194 1 precision precision NOUN cana-572 194 2 = = SYM cana-572 194 3 𝐓𝐏 𝐓𝐏 PROPN cana-572 194 4 𝐓𝐏+𝐅𝐏 𝐓𝐏+𝐅𝐏 VERB cana-572 194 5 recall,-recall recall,-recall NOUN cana-572 194 6 , , PUNCT cana-572 194 7 in in ADP cana-572 194 8 classification classification NOUN cana-572 194 9 tasks task NOUN cana-572 194 10 , , PUNCT cana-572 194 11 a a DET cana-572 194 12 performance performance NOUN cana-572 194 13 indicator indicator NOUN cana-572 194 14 that that PRON cana-572 194 15 is be AUX cana-572 194 16 also also ADV cana-572 194 17 known know VERB cana-572 194 18 as as ADP cana-572 194 19 sensitivity sensitivity NOUN cana-572 194 20 or or CCONJ cana-572 194 21 true true ADJ cana-572 194 22 positive positive ADJ cana-572 194 23 rate rate NOUN cana-572 194 24 is be AUX cana-572 194 25 utilized utilize VERB cana-572 194 26 to to PART cana-572 194 27 evaluate evaluate VERB cana-572 194 28 the the DET cana-572 194 29 capability capability NOUN cana-572 194 30 of of ADP cana-572 194 31 a a DET cana-572 194 32 model model NOUN cana-572 194 33 to to PART cana-572 194 34 accurately accurately ADV cana-572 194 35 identify identify VERB cana-572 194 36 all all DET cana-572 194 37 positive positive ADJ cana-572 194 38 cases case NOUN cana-572 194 39 from from ADP cana-572 194 40 the the DET cana-572 194 41 entire entire ADJ cana-572 194 42 number number NOUN cana-572 194 43 of of ADP cana-572 194 44 actual actual ADJ cana-572 194 45 positive positive ADJ cana-572 194 46 examples example NOUN cana-572 194 47 that that PRON cana-572 194 48 are be AUX cana-572 194 49 contained contain VERB cana-572 194 50 inside inside ADP cana-572 194 51 the the DET cana-572 194 52 dataset dataset NOUN cana-572 194 53 . . PUNCT cana-572 195 1 a a DET cana-572 195 2 formula formula NOUN cana-572 195 3 that that PRON cana-572 195 4 is be AUX cana-572 195 5 used use VERB cana-572 195 6 to to PART cana-572 195 7 compute compute VERB cana-572 195 8 it it PRON cana-572 195 9 is be AUX cana-572 195 10 as as SCONJ cana-572 195 11 follows follow VERB cana-572 195 12 : : PUNCT cana-572 195 13 recall-= recall-= PROPN cana-572 195 14 𝐓𝐏 𝐓𝐏 PROPN cana-572 195 15 𝐓𝐏+𝐅𝐍 𝐓𝐏+𝐅𝐍 NOUN cana-572 195 16 table table NOUN cana-572 195 17 1 1 NUM cana-572 195 18 shows show VERB cana-572 195 19 a a DET cana-572 195 20 full full ADJ cana-572 195 21 comparison comparison NOUN cana-572 195 22 of of ADP cana-572 195 23 how how SCONJ cana-572 195 24 well well ADV cana-572 195 25 different different ADJ cana-572 195 26 machine machine NOUN cana-572 195 27 learning learn VERB cana-572 195 28 classifiers classifier NOUN cana-572 195 29 ( ( PUNCT cana-572 195 30 svm svm PROPN cana-572 195 31 , , PUNCT cana-572 195 32 knn knn PROPN cana-572 195 33 , , PUNCT cana-572 195 34 lr lr INTJ cana-572 195 35 , , PUNCT cana-572 195 36 rf rf ADJ cana-572 195 37 , , PUNCT cana-572 195 38 and and CCONJ cana-572 195 39 ann ann PROPN cana-572 195 40 ) ) PUNCT cana-572 195 41 worked work VERB cana-572 195 42 when when SCONJ cana-572 195 43 trained train VERB cana-572 195 44 with with ADP cana-572 195 45 different different ADJ cana-572 195 46 optimization optimization NOUN cana-572 195 47 algorithms algorithm NOUN cana-572 195 48 ( ( PUNCT cana-572 195 49 pso pso NOUN cana-572 195 50 , , PUNCT cana-572 195 51 gwo gwo PROPN cana-572 195 52 , , PUNCT cana-572 195 53 and and CCONJ cana-572 195 54 hpsogwo hpsogwo ADJ cana-572 195 55 ) ) PUNCT cana-572 195 56 and and CCONJ cana-572 195 57 when when SCONJ cana-572 195 58 the the DET cana-572 195 59 train train NOUN cana-572 195 60 - - PUNCT cana-572 195 61 test test NOUN cana-572 195 62 ratios ratio NOUN cana-572 195 63 were be AUX cana-572 195 64 90 90 NUM cana-572 195 65 - - SYM cana-572 195 66 10 10 NUM cana-572 195 67 , , PUNCT cana-572 195 68 80 80 NUM cana-572 195 69 - - SYM cana-572 195 70 20 20 NUM cana-572 195 71 , , PUNCT cana-572 195 72 70 70 NUM cana-572 195 73 - - SYM cana-572 195 74 30 30 NUM cana-572 195 75 , , PUNCT cana-572 195 76 and and CCONJ cana-572 195 77 60 60 NUM cana-572 195 78 - - SYM cana-572 195 79 40 40 NUM cana-572 195 80 . . PUNCT cana-572 196 1 for for ADP cana-572 196 2 each each DET cana-572 196 3 combination combination NOUN cana-572 196 4 of of ADP cana-572 196 5 classifier classifier NOUN cana-572 196 6 , , PUNCT cana-572 196 7 optimization optimization NOUN cana-572 196 8 algorithm algorithm NOUN cana-572 196 9 , , PUNCT cana-572 196 10 and and CCONJ cana-572 196 11 train train NOUN cana-572 196 12 - - PUNCT cana-572 196 13 test test NOUN cana-572 196 14 ratio ratio NOUN cana-572 196 15 , , PUNCT cana-572 196 16 the the DET cana-572 196 17 table table NOUN cana-572 196 18 reports report NOUN cana-572 196 19 accuracy accuracy NOUN cana-572 196 20 , , PUNCT cana-572 196 21 precision precision NOUN cana-572 196 22 , , PUNCT cana-572 196 23 and and CCONJ cana-572 196 24 recall recall NOUN cana-572 196 25 values value NOUN cana-572 196 26 . . PUNCT cana-572 197 1 fig fig NOUN cana-572 197 2 . . PUNCT cana-572 198 1 2 2 NUM cana-572 198 2 , , PUNCT cana-572 198 3 fig fig NOUN cana-572 198 4 . . PUNCT cana-572 199 1 3 3 NUM cana-572 199 2 , , PUNCT cana-572 199 3 and and CCONJ cana-572 199 4 fig fig NOUN cana-572 199 5 . . PUNCT cana-572 200 1 4 4 NUM cana-572 200 2 show show VERB cana-572 200 3 the the DET cana-572 200 4 support support NOUN cana-572 200 5 vector vector NOUN cana-572 200 6 machine machine NOUN cana-572 200 7 ( ( PUNCT cana-572 200 8 svm svm ADJ cana-572 200 9 ) ) PUNCT cana-572 200 10 performance performance NOUN cana-572 200 11 . . PUNCT cana-572 201 1 across across ADP cana-572 201 2 all all DET cana-572 201 3 train train NOUN cana-572 201 4 - - PUNCT cana-572 201 5 test test NOUN cana-572 201 6 split split NOUN cana-572 201 7 ratios ratio NOUN cana-572 201 8 , , PUNCT cana-572 201 9 svm svm ADJ cana-572 201 10 classifiers classifier NOUN cana-572 201 11 trained train VERB cana-572 201 12 with with ADP cana-572 201 13 the the DET cana-572 201 14 gwo gwo PROPN cana-572 201 15 optimization optimization NOUN cana-572 201 16 algorithm algorithm NOUN cana-572 201 17 consistently consistently ADV cana-572 201 18 achieved achieve VERB cana-572 201 19 the the DET cana-572 201 20 highest high ADJ cana-572 201 21 accuracy accuracy NOUN cana-572 201 22 , , PUNCT cana-572 201 23 precision precision NOUN cana-572 201 24 , , PUNCT cana-572 201 25 and and CCONJ cana-572 201 26 recall recall NOUN cana-572 201 27 values value NOUN cana-572 201 28 . . PUNCT cana-572 202 1 in in ADP cana-572 202 2 the the DET cana-572 202 3 90 90 NUM cana-572 202 4 - - SYM cana-572 202 5 10 10 NUM cana-572 202 6 split split NOUN cana-572 202 7 , , PUNCT cana-572 202 8 gwo gwo PROPN cana-572 202 9 attained attain VERB cana-572 202 10 an an DET cana-572 202 11 accuracy accuracy NOUN cana-572 202 12 of of ADP cana-572 202 13 96.49 96.49 NUM cana-572 202 14 % % NOUN cana-572 202 15 , , PUNCT cana-572 202 16 precision precision NOUN cana-572 202 17 of of ADP cana-572 202 18 97.22 97.22 NUM cana-572 202 19 % % NOUN cana-572 202 20 , , PUNCT cana-572 202 21 and and CCONJ cana-572 202 22 recall recall NOUN cana-572 202 23 of of ADP cana-572 202 24 97.22 97.22 NUM cana-572 202 25 % % NOUN cana-572 202 26 . . PUNCT cana-572 203 1 and and CCONJ cana-572 203 2 fig fig NOUN cana-572 203 3 . . PUNCT cana-572 204 1 5 5 NUM cana-572 204 2 , , PUNCT cana-572 204 3 6 6 NUM cana-572 204 4 , , PUNCT cana-572 204 5 and and CCONJ cana-572 204 6 7 7 NUM cana-572 204 7 shows show VERB cana-572 204 8 the the DET cana-572 204 9 k k NOUN cana-572 204 10 - - PUNCT cana-572 204 11 nearest near ADJ cana-572 204 12 neighbors neighbor NOUN cana-572 204 13 ( ( PUNCT cana-572 204 14 knn knn NOUN cana-572 204 15 ) ) PUNCT cana-572 204 16 performance performance NOUN cana-572 204 17 , , PUNCT cana-572 204 18 with with ADP cana-572 204 19 gwo gwo PROPN cana-572 204 20 consistently consistently ADV cana-572 204 21 demonstrating demonstrate VERB cana-572 204 22 strong strong ADJ cana-572 204 23 accuracy accuracy NOUN cana-572 204 24 , , PUNCT cana-572 204 25 precision precision NOUN cana-572 204 26 , , PUNCT cana-572 204 27 and and CCONJ cana-572 204 28 recall recall NOUN cana-572 204 29 rates rate NOUN cana-572 204 30 across across ADP cana-572 204 31 different different ADJ cana-572 204 32 split split NOUN cana-572 204 33 ratios ratio NOUN cana-572 204 34 . . PUNCT cana-572 205 1 in in ADP cana-572 205 2 the the DET cana-572 205 3 90 90 NUM cana-572 205 4 - - SYM cana-572 205 5 10 10 NUM cana-572 205 6 split split NOUN cana-572 205 7 , , PUNCT cana-572 205 8 gwo gwo PROPN cana-572 205 9 achieved achieve VERB cana-572 205 10 an an DET cana-572 205 11 accuracy accuracy NOUN cana-572 205 12 of of ADP cana-572 205 13 98.25 98.25 NUM cana-572 205 14 % % NOUN cana-572 205 15 , , PUNCT cana-572 205 16 precision precision NOUN cana-572 205 17 of of ADP cana-572 205 18 97.30 97.30 NUM cana-572 205 19 % % NOUN cana-572 205 20 , , PUNCT cana-572 205 21 and and CCONJ cana-572 205 22 recall recall NOUN cana-572 205 23 of of ADP cana-572 205 24 99.00 99.00 NUM cana-572 205 25 % % NOUN cana-572 205 26 . . PUNCT cana-572 206 1 and and CCONJ cana-572 206 2 fig fig NOUN cana-572 206 3 . . PUNCT cana-572 207 1 8 8 NUM cana-572 207 2 ; ; PUNCT cana-572 207 3 fig fig NOUN cana-572 207 4 . . PUNCT cana-572 208 1 9 9 NUM cana-572 208 2 ; ; PUNCT cana-572 208 3 and and CCONJ cana-572 208 4 fig fig NOUN cana-572 208 5 . . PUNCT cana-572 209 1 10 10 NUM cana-572 209 2 show show VERB cana-572 209 3 the the DET cana-572 209 4 logistic logistic ADJ cana-572 209 5 regression regression NOUN cana-572 209 6 ( ( PUNCT cana-572 209 7 lr lr NOUN cana-572 209 8 ) ) PUNCT cana-572 209 9 performance performance NOUN cana-572 209 10 . . PUNCT cana-572 210 1 lr lr NOUN cana-572 210 2 classifiers classifier NOUN cana-572 210 3 trained train VERB cana-572 210 4 with with ADP cana-572 210 5 the the DET cana-572 210 6 pso pso NOUN cana-572 210 7 optimization optimization NOUN cana-572 210 8 algorithm algorithm NOUN cana-572 210 9 consistently consistently ADV cana-572 210 10 achieved achieve VERB cana-572 210 11 high high ADJ cana-572 210 12 accuracy accuracy NOUN cana-572 210 13 and and CCONJ cana-572 210 14 precision precision NOUN cana-572 210 15 values value NOUN cana-572 210 16 across across ADP cana-572 210 17 various various ADJ cana-572 210 18 split split ADJ cana-572 210 19 ratios ratio NOUN cana-572 210 20 . . PUNCT cana-572 211 1 for for ADP cana-572 211 2 instance instance NOUN cana-572 211 3 , , PUNCT cana-572 211 4 in in ADP cana-572 211 5 the the DET cana-572 211 6 90 90 NUM cana-572 211 7 - - SYM cana-572 211 8 10 10 NUM cana-572 211 9 split split NOUN cana-572 211 10 , , PUNCT cana-572 211 11 pso pso NOUN cana-572 211 12 attained attain VERB cana-572 211 13 an an DET cana-572 211 14 accuracy accuracy NOUN cana-572 211 15 of of ADP cana-572 211 16 98.25 98.25 NUM cana-572 211 17 % % NOUN cana-572 211 18 and and CCONJ cana-572 211 19 precision precision NOUN cana-572 211 20 of of ADP cana-572 211 21 97.30 97.30 NUM cana-572 211 22 % % NOUN cana-572 211 23 . . PUNCT cana-572 212 1 and and CCONJ cana-572 212 2 fig fig NOUN cana-572 212 3 . . PUNCT cana-572 213 1 11 11 NUM cana-572 213 2 , , PUNCT cana-572 213 3 12 12 NUM cana-572 213 4 , , PUNCT cana-572 213 5 and and CCONJ cana-572 213 6 13 13 NUM cana-572 213 7 show show VERB cana-572 213 8 the the DET cana-572 213 9 random random ADJ cana-572 213 10 forest forest NOUN cana-572 213 11 ( ( PUNCT cana-572 213 12 rf rf NOUN cana-572 213 13 ) ) PUNCT cana-572 213 14 performance performance NOUN cana-572 213 15 . . PUNCT cana-572 214 1 rf rf NOUN cana-572 214 2 classifiers classifier NOUN cana-572 214 3 trained train VERB cana-572 214 4 with with ADP cana-572 214 5 the the DET cana-572 214 6 pso pso NOUN cana-572 214 7 and and CCONJ cana-572 214 8 hpsogwo hpsogwo ADJ cana-572 214 9 algorithms algorithm NOUN cana-572 214 10 demonstrated demonstrate VERB cana-572 214 11 competitive competitive ADJ cana-572 214 12 precision precision NOUN cana-572 214 13 rates rate NOUN cana-572 214 14 across across ADP cana-572 214 15 all all DET cana-572 214 16 split split ADJ cana-572 214 17 ratios ratio NOUN cana-572 214 18 . . PUNCT cana-572 215 1 gwo gwo PROPN cana-572 215 2 also also ADV cana-572 215 3 performed perform VERB cana-572 215 4 well well ADV cana-572 215 5 , , PUNCT cana-572 215 6 particularly particularly ADV cana-572 215 7 in in ADP cana-572 215 8 achieving achieve VERB cana-572 215 9 high high ADJ cana-572 215 10 recall recall NOUN cana-572 215 11 rates rate NOUN cana-572 215 12 . . PUNCT cana-572 216 1 in in ADP cana-572 216 2 fig fig NOUN cana-572 216 3 . . PUNCT cana-572 217 1 14 14 NUM cana-572 217 2 , , PUNCT cana-572 217 3 fig fig NOUN cana-572 217 4 . . PUNCT cana-572 217 5 15 15 NUM cana-572 217 6 , , PUNCT cana-572 217 7 and and CCONJ cana-572 217 8 fig fig NOUN cana-572 217 9 . . PUNCT cana-572 218 1 16 16 NUM cana-572 218 2 , , PUNCT cana-572 218 3 showing show VERB cana-572 218 4 the the DET cana-572 218 5 artificial artificial ADJ cana-572 218 6 neural neural ADJ cana-572 218 7 network network NOUN cana-572 218 8 performance performance NOUN cana-572 218 9 , , PUNCT cana-572 218 10 ann ann PROPN cana-572 218 11 classifiers classifier NOUN cana-572 218 12 exhibited exhibit VERB cana-572 218 13 strong strong ADJ cana-572 218 14 performance performance NOUN cana-572 218 15 across across ADP cana-572 218 16 different different ADJ cana-572 218 17 optimization optimization NOUN cana-572 218 18 algorithms algorithm NOUN cana-572 218 19 and and CCONJ cana-572 218 20 split split ADJ cana-572 218 21 ratios ratio NOUN cana-572 218 22 . . PUNCT cana-572 219 1 hpsogwo hpsogwo PROPN cana-572 219 2 consistently consistently ADV cana-572 219 3 achieved achieve VERB cana-572 219 4 high high ADJ cana-572 219 5 accuracy accuracy NOUN cana-572 219 6 , , PUNCT cana-572 219 7 precision precision NOUN cana-572 219 8 , , PUNCT cana-572 219 9 and and CCONJ cana-572 219 10 recall recall NOUN cana-572 219 11 rates rate NOUN cana-572 219 12 across across ADP cana-572 219 13 all all DET cana-572 219 14 splits split NOUN cana-572 219 15 , , PUNCT cana-572 219 16 showcasing showcase VERB cana-572 219 17 its its PRON cana-572 219 18 effectiveness effectiveness NOUN cana-572 219 19 . . PUNCT cana-572 220 1 communications communication NOUN cana-572 220 2 on on ADP cana-572 220 3 applied apply VERB cana-572 220 4 nonlinear nonlinear ADJ cana-572 220 5 analysis analysis NOUN cana-572 220 6 issn issn NOUN cana-572 220 7 : : PUNCT cana-572 220 8 1074 1074 NUM cana-572 220 9 - - PUNCT cana-572 220 10 133x 133x NUM cana-572 220 11 vol vol NOUN cana-572 220 12 31 31 NUM cana-572 220 13 no no NOUN cana-572 220 14 . . NOUN cana-572 220 15 2 2 NUM cana-572 220 16 ( ( PUNCT cana-572 220 17 2024 2024 NUM cana-572 220 18 ) ) PUNCT cana-572 220 19 344 344 NUM cana-572 220 20 https://internationalpubls.com https://internationalpubls.com X cana-572 220 21 fig fig NOUN cana-572 220 22 . . PUNCT cana-572 221 1 2 2 NUM cana-572 221 2 svm svm ADJ cana-572 221 3 accuracy accuracy NOUN cana-572 221 4 for for ADP cana-572 221 5 different different ADJ cana-572 221 6 training training NOUN cana-572 221 7 testing testing NOUN cana-572 221 8 ratio ratio NOUN cana-572 221 9 fig fig NOUN cana-572 221 10 . . PUNCT cana-572 222 1 3 3 NUM cana-572 222 2 svm svm PROPN cana-572 222 3 precision precision NOUN cana-572 222 4 for for ADP cana-572 222 5 different different ADJ cana-572 222 6 training training NOUN cana-572 222 7 testing testing NOUN cana-572 222 8 ratios ratio NOUN cana-572 222 9 fig fig NOUN cana-572 222 10 . . PUNCT cana-572 222 11 4 4 NUM cana-572 222 12 svm svm PROPN cana-572 222 13 recall recall NOUN cana-572 222 14 for for ADP cana-572 222 15 different different ADJ cana-572 222 16 training training NOUN cana-572 222 17 testing testing NOUN cana-572 222 18 ratio ratio NOUN cana-572 222 19 88.00 88.00 NUM cana-572 222 20 90.00 90.00 NUM cana-572 222 21 92.00 92.00 NUM cana-572 222 22 94.00 94.00 NUM cana-572 222 23 96.00 96.00 NUM cana-572 222 24 98.00 98.00 NUM cana-572 222 25 100.00 100.00 NUM cana-572 222 26 acc_all acc_all NOUN cana-572 222 27 acc_gwo acc_gwo ADJ cana-572 222 28 acc_pso acc_pso PROPN cana-572 222 29 acc_hpsogwo acc_hpsogwo NOUN cana-572 222 30 % % NOUN cana-572 222 31 proposed propose VERB cana-572 222 32 optimization optimization NOUN cana-572 222 33 svm svm NOUN cana-572 222 34 accuracy accuracy NOUN cana-572 222 35 for for ADP cana-572 222 36 different different ADJ cana-572 222 37 training training NOUN cana-572 222 38 testing testing NOUN cana-572 222 39 ratio ratio NOUN cana-572 222 40 90 90 NUM cana-572 222 41 - - SYM cana-572 222 42 10 10 NUM cana-572 222 43 80 80 NUM cana-572 222 44 - - SYM cana-572 222 45 20 20 NUM cana-572 222 46 70 70 NUM cana-572 222 47 - - SYM cana-572 222 48 30 30 NUM cana-572 222 49 60 60 NUM cana-572 222 50 - - SYM cana-572 222 51 40 40 NUM cana-572 222 52 95.50 95.50 NUM cana-572 222 53 96.00 96.00 NUM cana-572 222 54 96.50 96.50 NUM cana-572 222 55 97.00 97.00 NUM cana-572 222 56 97.50 97.50 NUM cana-572 222 57 98.00 98.00 NUM cana-572 222 58 98.50 98.50 NUM cana-572 222 59 99.00 99.00 NUM cana-572 222 60 pre_all pre_all NOUN cana-572 222 61 pre_gwo pre_gwo ADJ cana-572 222 62 pre_pso pre_pso PROPN cana-572 222 63 pre_hpsogwo pre_hpsogwo ADJ cana-572 222 64 % % NOUN cana-572 222 65 proposed propose VERB cana-572 222 66 optimization optimization NOUN cana-572 222 67 svm svm PROPN cana-572 222 68 precision precision NOUN cana-572 222 69 fordifferenttraining fordifferenttraining NOUN cana-572 222 70 testing testing NOUN cana-572 222 71 ratio ratio NOUN cana-572 222 72 90 90 NUM cana-572 222 73 - - SYM cana-572 222 74 10 10 NUM cana-572 222 75 80 80 NUM cana-572 222 76 - - SYM cana-572 222 77 20 20 NUM cana-572 222 78 70 70 NUM cana-572 222 79 - - SYM cana-572 222 80 30 30 NUM cana-572 222 81 60 60 NUM cana-572 222 82 - - SYM cana-572 222 83 40 40 NUM cana-572 222 84 95.00 95.00 NUM cana-572 222 85 96.00 96.00 NUM cana-572 222 86 97.00 97.00 NUM cana-572 222 87 98.00 98.00 NUM cana-572 222 88 99.00 99.00 NUM cana-572 222 89 pre_all pre_all NOUN cana-572 222 90 pre_gwo pre_gwo ADJ cana-572 222 91 pre_pso pre_pso PROPN cana-572 222 92 pre_hpsogwo pre_hpsogwo ADJ cana-572 222 93 % % NOUN cana-572 222 94 proposed propose VERB cana-572 222 95 optimization optimization NOUN cana-572 222 96 svm svm PROPN cana-572 222 97 precision precision NOUN cana-572 222 98 fordifferenttraining fordifferenttraining NOUN cana-572 222 99 testing testing NOUN cana-572 222 100 ratio ratio NOUN cana-572 222 101 90 90 NUM cana-572 222 102 - - SYM cana-572 222 103 10 10 NUM cana-572 222 104 80 80 NUM cana-572 222 105 - - SYM cana-572 222 106 20 20 NUM cana-572 222 107 70 70 NUM cana-572 222 108 - - SYM cana-572 222 109 30 30 NUM cana-572 222 110 60 60 NUM cana-572 222 111 - - SYM cana-572 222 112 40 40 NUM cana-572 222 113 communications communication NOUN cana-572 222 114 on on ADP cana-572 222 115 applied apply VERB cana-572 222 116 nonlinear nonlinear ADJ cana-572 222 117 analysis analysis NOUN cana-572 222 118 issn issn NOUN cana-572 222 119 : : PUNCT cana-572 222 120 1074 1074 NUM cana-572 222 121 - - PUNCT cana-572 222 122 133x 133x NUM cana-572 222 123 vol vol NOUN cana-572 222 124 31 31 NUM cana-572 222 125 no no NOUN cana-572 222 126 . . NOUN cana-572 222 127 2 2 NUM cana-572 222 128 ( ( PUNCT cana-572 222 129 2024 2024 NUM cana-572 222 130 ) ) PUNCT cana-572 222 131 345 345 NUM cana-572 222 132 https://internationalpubls.com https://internationalpubls.com X cana-572 222 133 fig.5 fig.5 NOUN cana-572 222 134 knn knn NOUN cana-572 222 135 accuracy accuracy NOUN cana-572 222 136 for for ADP cana-572 222 137 different different ADJ cana-572 222 138 training training NOUN cana-572 222 139 testing testing NOUN cana-572 222 140 ratio ratio NOUN cana-572 222 141 fig.6 fig.6 PROPN cana-572 222 142 knn knn PROPN cana-572 222 143 precision precision NOUN cana-572 222 144 for for ADP cana-572 222 145 different different ADJ cana-572 222 146 training training NOUN cana-572 222 147 testing testing NOUN cana-572 222 148 ratio ratio NOUN cana-572 222 149 fig.7 fig.7 PROPN cana-572 222 150 knn knn PROPN cana-572 222 151 recall recall PROPN cana-572 222 152 for for ADP cana-572 222 153 different different ADJ cana-572 222 154 training training NOUN cana-572 222 155 testing testing NOUN cana-572 222 156 ratio ratio NOUN cana-572 222 157 90.00 90.00 NUM cana-572 222 158 92.00 92.00 NUM cana-572 222 159 94.00 94.00 NUM cana-572 222 160 96.00 96.00 NUM cana-572 222 161 98.00 98.00 NUM cana-572 222 162 100.00 100.00 NUM cana-572 222 163 acc_all acc_all NOUN cana-572 222 164 acc_gwo acc_gwo ADJ cana-572 222 165 acc_pso acc_pso PROPN cana-572 222 166 acc_hpsogwo acc_hpsogwo NOUN cana-572 222 167 % % NOUN cana-572 222 168 proposed propose VERB cana-572 222 169 optimization optimization NOUN cana-572 222 170 knn knn PROPN cana-572 222 171 accuracy accuracy NOUN cana-572 222 172 for for ADP cana-572 222 173 different different ADJ cana-572 222 174 training training NOUN cana-572 222 175 testing testing NOUN cana-572 222 176 ratio ratio NOUN cana-572 222 177 90 90 NUM cana-572 222 178 - - SYM cana-572 222 179 10 10 NUM cana-572 222 180 80 80 NUM cana-572 222 181 - - SYM cana-572 222 182 20 20 NUM cana-572 222 183 70 70 NUM cana-572 222 184 - - SYM cana-572 222 185 30 30 NUM cana-572 222 186 60 60 NUM cana-572 222 187 - - SYM cana-572 222 188 40 40 NUM cana-572 222 189 93.00 93.00 NUM cana-572 222 190 94.00 94.00 NUM cana-572 222 191 95.00 95.00 NUM cana-572 222 192 96.00 96.00 NUM cana-572 222 193 97.00 97.00 NUM cana-572 222 194 98.00 98.00 NUM cana-572 222 195 pre_all pre_all NOUN cana-572 222 196 pre_gwo pre_gwo ADJ cana-572 222 197 pre_pso pre_pso PROPN cana-572 222 198 pre_hpsogwo pre_hpsogwo ADJ cana-572 222 199 % % NOUN cana-572 222 200 proposed propose VERB cana-572 222 201 optimization optimization NOUN cana-572 222 202 knn knn PROPN cana-572 222 203 precision precision PROPN cana-572 222 204 for for ADP cana-572 222 205 different different ADJ cana-572 222 206 training training NOUN cana-572 222 207 testing testing NOUN cana-572 222 208 ratio ratio NOUN cana-572 222 209 90 90 NUM cana-572 222 210 - - SYM cana-572 222 211 10 10 NUM cana-572 222 212 80 80 NUM cana-572 222 213 - - SYM cana-572 222 214 20 20 NUM cana-572 222 215 70 70 NUM cana-572 222 216 - - SYM cana-572 222 217 30 30 NUM cana-572 222 218 60 60 NUM cana-572 222 219 - - SYM cana-572 222 220 40 40 NUM cana-572 222 221 88.00 88.00 NUM cana-572 222 222 90.00 90.00 NUM cana-572 222 223 92.00 92.00 NUM cana-572 222 224 94.00 94.00 NUM cana-572 222 225 96.00 96.00 NUM cana-572 222 226 98.00 98.00 NUM cana-572 222 227 100.00 100.00 NUM cana-572 222 228 102.00 102.00 NUM cana-572 222 229 rcall_all rcall_all NOUN cana-572 222 230 rcall_gwo rcall_gwo NUM cana-572 222 231 rcall_pso rcall_pso NUM cana-572 222 232 rcall_hpsogwo rcall_hpsogwo ADJ cana-572 222 233 % % NOUN cana-572 222 234 proposed propose VERB cana-572 222 235 optimization optimization NOUN cana-572 222 236 knn knn PROPN cana-572 222 237 recall recall PROPN cana-572 222 238 for for ADP cana-572 222 239 different different ADJ cana-572 222 240 training training NOUN cana-572 222 241 testing testing NOUN cana-572 222 242 ratio ratio NOUN cana-572 222 243 90 90 NUM cana-572 222 244 - - SYM cana-572 222 245 10 10 NUM cana-572 222 246 80 80 NUM cana-572 222 247 - - SYM cana-572 222 248 20 20 NUM cana-572 222 249 70 70 NUM cana-572 222 250 - - SYM cana-572 222 251 30 30 NUM cana-572 222 252 60 60 NUM cana-572 222 253 - - SYM cana-572 222 254 40 40 NUM cana-572 222 255 communications communication NOUN cana-572 222 256 on on ADP cana-572 222 257 applied apply VERB cana-572 222 258 nonlinear nonlinear ADJ cana-572 222 259 analysis analysis NOUN cana-572 222 260 issn issn NOUN cana-572 222 261 : : PUNCT cana-572 222 262 1074 1074 NUM cana-572 222 263 - - PUNCT cana-572 222 264 133x 133x NUM cana-572 222 265 vol vol NOUN cana-572 222 266 31 31 NUM cana-572 222 267 no no NOUN cana-572 222 268 . . NOUN cana-572 222 269 2 2 NUM cana-572 222 270 ( ( PUNCT cana-572 222 271 2024 2024 NUM cana-572 222 272 ) ) PUNCT cana-572 222 273 346 346 NUM cana-572 222 274 https://internationalpubls.com https://internationalpubls.com X cana-572 222 275 fig.8 fig.8 PROPN cana-572 222 276 lr lr NOUN cana-572 222 277 accuracy accuracy NOUN cana-572 222 278 for for ADP cana-572 222 279 different different ADJ cana-572 222 280 training training NOUN cana-572 222 281 testing testing NOUN cana-572 222 282 ratio ratio NOUN cana-572 222 283 fig.9 fig.9 PROPN cana-572 222 284 lr lr PROPN cana-572 222 285 precision precision NOUN cana-572 222 286 for for ADP cana-572 222 287 different different ADJ cana-572 222 288 training training NOUN cana-572 222 289 testing testing NOUN cana-572 222 290 ratio ratio NOUN cana-572 222 291 fig.10 fig.10 PROPN cana-572 222 292 lr lr NOUN cana-572 222 293 recall recall NOUN cana-572 222 294 for for ADP cana-572 222 295 different different ADJ cana-572 222 296 training training NOUN cana-572 222 297 testing testing NOUN cana-572 222 298 ratio ratio NOUN cana-572 222 299 90.00 90.00 NUM cana-572 222 300 92.00 92.00 NUM cana-572 222 301 94.00 94.00 NUM cana-572 222 302 96.00 96.00 NUM cana-572 222 303 98.00 98.00 NUM cana-572 222 304 100.00 100.00 NUM cana-572 222 305 acc_all acc_all NOUN cana-572 222 306 acc_gwo acc_gwo ADJ cana-572 222 307 acc_pso acc_pso PROPN cana-572 222 308 acc_hpsogwo acc_hpsogwo NOUN cana-572 222 309 % % NOUN cana-572 222 310 proposed propose VERB cana-572 222 311 optimization optimization NOUN cana-572 222 312 lr lr NOUN cana-572 222 313 accuracy accuracy NOUN cana-572 222 314 for for ADP cana-572 222 315 different different ADJ cana-572 222 316 training training NOUN cana-572 222 317 testing testing NOUN cana-572 222 318 ratio ratio NOUN cana-572 222 319 90 90 NUM cana-572 222 320 - - SYM cana-572 222 321 10 10 NUM cana-572 222 322 80 80 NUM cana-572 222 323 - - SYM cana-572 222 324 20 20 NUM cana-572 222 325 70 70 NUM cana-572 222 326 - - SYM cana-572 222 327 30 30 NUM cana-572 222 328 60 60 NUM cana-572 222 329 - - SYM cana-572 222 330 40 40 NUM cana-572 222 331 88.00 88.00 NUM cana-572 222 332 90.00 90.00 NUM cana-572 222 333 92.00 92.00 NUM cana-572 222 334 94.00 94.00 NUM cana-572 222 335 96.00 96.00 NUM cana-572 222 336 98.00 98.00 NUM cana-572 222 337 pre_all pre_all NOUN cana-572 222 338 pre_gwo pre_gwo ADJ cana-572 222 339 pre_pso pre_pso PROPN cana-572 222 340 pre_hpsogwo pre_hpsogwo ADJ cana-572 222 341 % % NOUN cana-572 222 342 proposed propose VERB cana-572 222 343 optimization optimization NOUN cana-572 222 344 lr lr NOUN cana-572 222 345 precision precision NOUN cana-572 222 346 for for ADP cana-572 222 347 different different ADJ cana-572 222 348 training training NOUN cana-572 222 349 testing testing NOUN cana-572 222 350 ratio ratio NOUN cana-572 222 351 90 90 NUM cana-572 222 352 - - SYM cana-572 222 353 10 10 NUM cana-572 222 354 80 80 NUM cana-572 222 355 - - SYM cana-572 222 356 20 20 NUM cana-572 222 357 70 70 NUM cana-572 222 358 - - SYM cana-572 222 359 30 30 NUM cana-572 222 360 60 60 NUM cana-572 222 361 - - SYM cana-572 222 362 40 40 NUM cana-572 222 363 86.00 86.00 NUM cana-572 222 364 88.00 88.00 NUM cana-572 222 365 90.00 90.00 NUM cana-572 222 366 92.00 92.00 NUM cana-572 222 367 94.00 94.00 NUM cana-572 222 368 96.00 96.00 NUM cana-572 222 369 98.00 98.00 NUM cana-572 222 370 100.00 100.00 NUM cana-572 222 371 rcall_all rcall_all NOUN cana-572 222 372 rcall_gwo rcall_gwo NUM cana-572 222 373 rcall_pso rcall_pso NUM cana-572 222 374 rcall_hpsogwo rcall_hpsogwo ADJ cana-572 222 375 % % NOUN cana-572 222 376 proposed propose VERB cana-572 222 377 optimization optimization NOUN cana-572 222 378 lr lr AUX cana-572 222 379 recall recall VERB cana-572 222 380 different different ADJ cana-572 222 381 training training NOUN cana-572 222 382 testing testing NOUN cana-572 222 383 ratio ratio NOUN cana-572 222 384 90 90 NUM cana-572 222 385 - - SYM cana-572 222 386 10 10 NUM cana-572 222 387 80 80 NUM cana-572 222 388 - - SYM cana-572 222 389 20 20 NUM cana-572 222 390 70 70 NUM cana-572 222 391 - - SYM cana-572 222 392 30 30 NUM cana-572 222 393 60 60 NUM cana-572 222 394 - - SYM cana-572 222 395 40 40 NUM cana-572 222 396 communications communication NOUN cana-572 222 397 on on ADP cana-572 222 398 applied apply VERB cana-572 222 399 nonlinear nonlinear ADJ cana-572 222 400 analysis analysis NOUN cana-572 222 401 issn issn NOUN cana-572 222 402 : : PUNCT cana-572 222 403 1074 1074 NUM cana-572 222 404 - - PUNCT cana-572 222 405 133x 133x NUM cana-572 222 406 vol vol NOUN cana-572 222 407 31 31 NUM cana-572 222 408 no no NOUN cana-572 222 409 . . NOUN cana-572 222 410 2 2 NUM cana-572 222 411 ( ( PUNCT cana-572 222 412 2024 2024 NUM cana-572 222 413 ) ) PUNCT cana-572 222 414 347 347 NUM cana-572 222 415 https://internationalpubls.com https://internationalpubls.com X cana-572 222 416 fig.11 fig.11 PROPN cana-572 222 417 rf rf ADJ cana-572 222 418 accuracy accuracy NOUN cana-572 222 419 for for ADP cana-572 222 420 different different ADJ cana-572 222 421 training training NOUN cana-572 222 422 testing testing NOUN cana-572 222 423 ratio ratio NOUN cana-572 222 424 fig.12 fig.12 NOUN cana-572 222 425 rf rf NOUN cana-572 222 426 precision precision NOUN cana-572 222 427 for for ADP cana-572 222 428 different different ADJ cana-572 222 429 training training NOUN cana-572 222 430 testing testing NOUN cana-572 222 431 ratio ratio NOUN cana-572 222 432 fig fig NOUN cana-572 222 433 . . PUNCT cana-572 223 1 13 13 NUM cana-572 223 2 rf rf NOUN cana-572 223 3 recall recall NOUN cana-572 223 4 for for ADP cana-572 223 5 different different ADJ cana-572 223 6 training training NOUN cana-572 223 7 testing testing NOUN cana-572 223 8 ratio ratio NOUN cana-572 223 9 91.00 91.00 NUM cana-572 223 10 92.00 92.00 NUM cana-572 223 11 93.00 93.00 NUM cana-572 223 12 94.00 94.00 NUM cana-572 223 13 95.00 95.00 NUM cana-572 223 14 96.00 96.00 NUM cana-572 223 15 97.00 97.00 NUM cana-572 224 1 acc_all acc_all NOUN cana-572 224 2 acc_gwo acc_gwo ADJ cana-572 224 3 acc_pso acc_pso PROPN cana-572 224 4 acc_hpsogwo acc_hpsogwo NOUN cana-572 224 5 % % NOUN cana-572 224 6 proposed propose VERB cana-572 224 7 optimization optimization NOUN cana-572 224 8 rf rf NOUN cana-572 224 9 accuracy accuracy NOUN cana-572 224 10 for for ADP cana-572 224 11 different different ADJ cana-572 224 12 training training NOUN cana-572 224 13 testing testing NOUN cana-572 224 14 ratio ratio NOUN cana-572 224 15 90 90 NUM cana-572 224 16 - - SYM cana-572 224 17 10 10 NUM cana-572 224 18 80 80 NUM cana-572 224 19 - - SYM cana-572 224 20 20 20 NUM cana-572 224 21 70 70 NUM cana-572 224 22 - - SYM cana-572 224 23 30 30 NUM cana-572 224 24 60 60 NUM cana-572 224 25 - - SYM cana-572 224 26 40 40 NUM cana-572 224 27 93.00 93.00 NUM cana-572 224 28 94.00 94.00 NUM cana-572 224 29 95.00 95.00 NUM cana-572 224 30 96.00 96.00 NUM cana-572 224 31 97.00 97.00 NUM cana-572 224 32 98.00 98.00 NUM cana-572 224 33 pre_all pre_all NOUN cana-572 224 34 pre_gwo pre_gwo ADJ cana-572 224 35 pre_pso pre_pso PROPN cana-572 224 36 pre_hpsogwo pre_hpsogwo ADJ cana-572 224 37 % % NOUN cana-572 224 38 proposed propose VERB cana-572 224 39 optimization optimization NOUN cana-572 224 40 rf rf NOUN cana-572 224 41 precision precision NOUN cana-572 224 42 for for ADP cana-572 224 43 different different ADJ cana-572 224 44 training training NOUN cana-572 224 45 testing testing NOUN cana-572 224 46 ratio ratio NOUN cana-572 224 47 90 90 NUM cana-572 224 48 - - SYM cana-572 224 49 10 10 NUM cana-572 224 50 80 80 NUM cana-572 224 51 - - SYM cana-572 224 52 20 20 NUM cana-572 224 53 70 70 NUM cana-572 224 54 - - SYM cana-572 224 55 30 30 NUM cana-572 224 56 60 60 NUM cana-572 224 57 - - SYM cana-572 224 58 40 40 NUM cana-572 224 59 88.00 88.00 NUM cana-572 224 60 90.00 90.00 NUM cana-572 224 61 92.00 92.00 NUM cana-572 224 62 94.00 94.00 NUM cana-572 224 63 96.00 96.00 NUM cana-572 224 64 98.00 98.00 NUM cana-572 224 65 100.00 100.00 NUM cana-572 224 66 rcall_all rcall_all NOUN cana-572 224 67 rcall_gwo rcall_gwo NUM cana-572 224 68 rcall_pso rcall_pso NUM cana-572 224 69 rcall_hpsogwo rcall_hpsogwo ADJ cana-572 224 70 % % NOUN cana-572 224 71 proposed propose VERB cana-572 224 72 optimization optimization NOUN cana-572 224 73 rf rf NOUN cana-572 224 74 recall recall NOUN cana-572 224 75 for for ADP cana-572 224 76 different different ADJ cana-572 224 77 training training NOUN cana-572 224 78 testing testing NOUN cana-572 224 79 ratio ratio NOUN cana-572 224 80 90 90 NUM cana-572 224 81 - - SYM cana-572 224 82 10 10 NUM cana-572 224 83 80 80 NUM cana-572 224 84 - - SYM cana-572 224 85 20 20 NUM cana-572 224 86 70 70 NUM cana-572 224 87 - - SYM cana-572 224 88 30 30 NUM cana-572 224 89 60 60 NUM cana-572 224 90 - - SYM cana-572 224 91 40 40 NUM cana-572 224 92 communications communication NOUN cana-572 224 93 on on ADP cana-572 224 94 applied apply VERB cana-572 224 95 nonlinear nonlinear ADJ cana-572 224 96 analysis analysis NOUN cana-572 224 97 issn issn NOUN cana-572 224 98 : : PUNCT cana-572 224 99 1074 1074 NUM cana-572 224 100 - - PUNCT cana-572 224 101 133x 133x NUM cana-572 224 102 vol vol NOUN cana-572 224 103 31 31 NUM cana-572 224 104 no no NOUN cana-572 224 105 . . NOUN cana-572 224 106 2 2 NUM cana-572 224 107 ( ( PUNCT cana-572 224 108 2024 2024 NUM cana-572 224 109 ) ) PUNCT cana-572 224 110 348 348 NUM cana-572 224 111 https://internationalpubls.com https://internationalpubls.com X cana-572 224 112 fig fig NOUN cana-572 224 113 . . PUNCT cana-572 225 1 14 14 NUM cana-572 225 2 accuracy accuracy NOUN cana-572 225 3 for for ADP cana-572 225 4 different different ADJ cana-572 225 5 training training NOUN cana-572 225 6 testing testing NOUN cana-572 225 7 ratio ratio NOUN cana-572 225 8 fig fig NOUN cana-572 225 9 . . PUNCT cana-572 226 1 15 15 NUM cana-572 226 2 ann ann PROPN cana-572 226 3 precision precision NOUN cana-572 226 4 for for ADP cana-572 226 5 different different ADJ cana-572 226 6 training training NOUN cana-572 226 7 testing testing NOUN cana-572 226 8 ratio ratio NOUN cana-572 226 9 fig.16 fig.16 PROPN cana-572 226 10 ann ann PROPN cana-572 226 11 recall recall PROPN cana-572 226 12 for for ADP cana-572 226 13 different different ADJ cana-572 226 14 training training NOUN cana-572 226 15 testing testing NOUN cana-572 226 16 ratio ratio NOUN cana-572 226 17 86.00 86.00 NUM cana-572 226 18 88.00 88.00 NUM cana-572 226 19 90.00 90.00 NUM cana-572 226 20 92.00 92.00 NUM cana-572 226 21 94.00 94.00 NUM cana-572 226 22 96.00 96.00 NUM cana-572 226 23 98.00 98.00 NUM cana-572 226 24 100.00 100.00 NUM cana-572 226 25 acc_all acc_all NOUN cana-572 226 26 acc_gwo acc_gwo ADJ cana-572 226 27 acc_pso acc_pso PROPN cana-572 226 28 acc_hpsogwo acc_hpsogwo NOUN cana-572 226 29 % % NOUN cana-572 226 30 proposed propose VERB cana-572 226 31 optimization optimization NOUN cana-572 226 32 ann ann PROPN cana-572 226 33 accuracy accuracy NOUN cana-572 226 34 for for ADP cana-572 226 35 different different ADJ cana-572 226 36 training training NOUN cana-572 226 37 testing testing NOUN cana-572 226 38 ratio ratio NOUN cana-572 226 39 90 90 NUM cana-572 226 40 - - SYM cana-572 226 41 10 10 NUM cana-572 226 42 80 80 NUM cana-572 226 43 - - SYM cana-572 226 44 20 20 NUM cana-572 226 45 70 70 NUM cana-572 226 46 - - SYM cana-572 226 47 30 30 NUM cana-572 226 48 60 60 NUM cana-572 226 49 - - SYM cana-572 226 50 40 40 NUM cana-572 226 51 93.00 93.00 NUM cana-572 226 52 94.00 94.00 NUM cana-572 226 53 95.00 95.00 NUM cana-572 226 54 96.00 96.00 NUM cana-572 226 55 97.00 97.00 NUM cana-572 226 56 98.00 98.00 NUM cana-572 226 57 99.00 99.00 NUM cana-572 226 58 100.00 100.00 NUM cana-572 226 59 pre_all pre_all NOUN cana-572 226 60 pre_gwo pre_gwo ADJ cana-572 226 61 pre_pso pre_pso PROPN cana-572 226 62 pre_hpsogwo pre_hpsogwo ADJ cana-572 226 63 % % NOUN cana-572 226 64 proposed propose VERB cana-572 226 65 optimization optimization NOUN cana-572 226 66 ann ann PROPN cana-572 226 67 precision precision NOUN cana-572 226 68 for for ADP cana-572 226 69 different different ADJ cana-572 226 70 training training NOUN cana-572 226 71 testing testing NOUN cana-572 226 72 ratio ratio NOUN cana-572 226 73 90 90 NUM cana-572 226 74 - - SYM cana-572 226 75 10 10 NUM cana-572 226 76 80 80 NUM cana-572 226 77 - - SYM cana-572 226 78 20 20 NUM cana-572 226 79 70 70 NUM cana-572 226 80 - - SYM cana-572 226 81 30 30 NUM cana-572 226 82 60 60 NUM cana-572 226 83 - - SYM cana-572 226 84 40 40 NUM cana-572 226 85 88.00 88.00 NUM cana-572 226 86 90.00 90.00 NUM cana-572 226 87 92.00 92.00 NUM cana-572 226 88 94.00 94.00 NUM cana-572 226 89 96.00 96.00 NUM cana-572 226 90 98.00 98.00 NUM cana-572 226 91 100.00 100.00 NUM cana-572 226 92 rcall_all rcall_all NOUN cana-572 226 93 rcall_gwo rcall_gwo NUM cana-572 226 94 rcall_pso rcall_pso NUM cana-572 226 95 rcall_hpsogwo rcall_hpsogwo ADJ cana-572 226 96 % % NOUN cana-572 226 97 proposed propose VERB cana-572 226 98 optimization optimization NOUN cana-572 226 99 ann ann PROPN cana-572 226 100 recall recall NOUN cana-572 226 101 for for ADP cana-572 226 102 different different ADJ cana-572 226 103 training training NOUN cana-572 226 104 testing testing NOUN cana-572 226 105 ratio ratio NOUN cana-572 226 106 90 90 NUM cana-572 226 107 - - SYM cana-572 226 108 10 10 NUM cana-572 226 109 80 80 NUM cana-572 226 110 - - SYM cana-572 226 111 20 20 NUM cana-572 226 112 70 70 NUM cana-572 226 113 - - SYM cana-572 226 114 30 30 NUM cana-572 226 115 60 60 NUM cana-572 226 116 - - SYM cana-572 226 117 40 40 NUM cana-572 226 118 communications communication NOUN cana-572 226 119 on on ADP cana-572 226 120 applied apply VERB cana-572 226 121 nonlinear nonlinear ADJ cana-572 226 122 analysis analysis NOUN cana-572 226 123 issn issn NOUN cana-572 226 124 : : PUNCT cana-572 226 125 1074 1074 NUM cana-572 226 126 - - PUNCT cana-572 226 127 133x 133x NUM cana-572 226 128 vol vol NOUN cana-572 226 129 31 31 NUM cana-572 226 130 no no NOUN cana-572 226 131 . . NOUN cana-572 226 132 2 2 NUM cana-572 226 133 ( ( PUNCT cana-572 226 134 2024 2024 NUM cana-572 226 135 ) ) PUNCT cana-572 226 136 349 349 NUM cana-572 226 137 https://internationalpubls.com https://internationalpubls.com X cana-572 226 138 table table NOUN cana-572 226 139 2 2 NUM cana-572 226 140 number number NOUN cana-572 226 141 of of ADP cana-572 226 142 features feature NOUN cana-572 226 143 selected select VERB cana-572 226 144 by by ADP cana-572 226 145 three three NUM cana-572 226 146 different different ADJ cana-572 226 147 feature feature NOUN cana-572 226 148 selection selection NOUN cana-572 226 149 methods method NOUN cana-572 226 150 pso pso PROPN cana-572 226 151 gwo gwo PROPN cana-572 226 152 hpsogwo hpsogwo PROPN cana-572 226 153 svm svm PROPN cana-572 226 154 13 13 NUM cana-572 226 155 13 13 NUM cana-572 226 156 12 12 NUM cana-572 226 157 knn knn NOUN cana-572 226 158 13 13 NUM cana-572 226 159 10 10 NUM cana-572 226 160 13 13 NUM cana-572 226 161 lr lr NOUN cana-572 226 162 15 15 NUM cana-572 226 163 8 8 NUM cana-572 226 164 14 14 NUM cana-572 226 165 rf rf NUM cana-572 226 166 11 11 NUM cana-572 226 167 10 10 NUM cana-572 226 168 15 15 NUM cana-572 226 169 ann ann PROPN cana-572 226 170 12 12 NUM cana-572 226 171 9 9 NUM cana-572 226 172 16 16 NUM cana-572 226 173 table table NOUN cana-572 226 174 2 2 NUM cana-572 226 175 provides provide VERB cana-572 226 176 the the DET cana-572 226 177 number number NOUN cana-572 226 178 of of ADP cana-572 226 179 features feature NOUN cana-572 226 180 selected select VERB cana-572 226 181 by by ADP cana-572 226 182 three three NUM cana-572 226 183 different different ADJ cana-572 226 184 feature feature NOUN cana-572 226 185 selection selection NOUN cana-572 226 186 methods method NOUN cana-572 226 187 . . PUNCT cana-572 227 1 for for ADP cana-572 227 2 svm svm PROPN cana-572 227 3 , , PUNCT cana-572 227 4 pso pso NOUN cana-572 227 5 and and CCONJ cana-572 227 6 gwo gwo PROPN cana-572 227 7 select select ADJ cana-572 227 8 13 13 NUM cana-572 227 9 features feature NOUN cana-572 227 10 each each PRON cana-572 227 11 , , PUNCT cana-572 227 12 while while SCONJ cana-572 227 13 hpsogwo hpsogwo ADJ cana-572 227 14 selects select VERB cana-572 227 15 12 12 NUM cana-572 227 16 features feature NOUN cana-572 227 17 . . PUNCT cana-572 228 1 for for ADP cana-572 228 2 knn knn PROPN cana-572 228 3 , , PUNCT cana-572 228 4 pso pso NOUN cana-572 228 5 and and CCONJ cana-572 228 6 hpsogwo hpsogwo ADV cana-572 228 7 select select VERB cana-572 228 8 13 13 NUM cana-572 228 9 features feature NOUN cana-572 228 10 each each PRON cana-572 228 11 , , PUNCT cana-572 228 12 while while SCONJ cana-572 228 13 gwo gwo PROPN cana-572 228 14 selects select VERB cana-572 228 15 10 10 NUM cana-572 228 16 features feature NOUN cana-572 228 17 . . PUNCT cana-572 229 1 for for ADP cana-572 229 2 lr lr PROPN cana-572 229 3 , , PUNCT cana-572 229 4 pso pso NOUN cana-572 229 5 selects select VERB cana-572 229 6 15 15 NUM cana-572 229 7 features feature NOUN cana-572 229 8 , , PUNCT cana-572 229 9 gwo gwo PROPN cana-572 229 10 selects select VERB cana-572 229 11 8 8 NUM cana-572 229 12 features feature NOUN cana-572 229 13 , , PUNCT cana-572 229 14 and and CCONJ cana-572 229 15 hpsogwo hpsogwo ADJ cana-572 229 16 selects select VERB cana-572 229 17 14 14 NUM cana-572 229 18 features feature NOUN cana-572 229 19 . . PUNCT cana-572 230 1 for for ADP cana-572 230 2 rf rf NOUN cana-572 230 3 , , PUNCT cana-572 230 4 pso pso NOUN cana-572 230 5 and and CCONJ cana-572 230 6 gwo gwo PROPN cana-572 230 7 select select ADJ cana-572 230 8 11 11 NUM cana-572 230 9 features feature NOUN cana-572 230 10 each each PRON cana-572 230 11 , , PUNCT cana-572 230 12 while while SCONJ cana-572 230 13 hpsogwo hpsogwo ADJ cana-572 230 14 selects select VERB cana-572 230 15 15 15 NUM cana-572 230 16 features feature NOUN cana-572 230 17 . . PUNCT cana-572 231 1 for for ADP cana-572 231 2 ann ann PROPN cana-572 231 3 , , PUNCT cana-572 231 4 pso pso NOUN cana-572 231 5 selects select VERB cana-572 231 6 12 12 NUM cana-572 231 7 features feature NOUN cana-572 231 8 , , PUNCT cana-572 231 9 gwo gwo PROPN cana-572 231 10 selects select VERB cana-572 231 11 9 9 NUM cana-572 231 12 features feature NOUN cana-572 231 13 , , PUNCT cana-572 231 14 and and CCONJ cana-572 231 15 hpsogwo hpsogwo ADJ cana-572 231 16 selects select VERB cana-572 231 17 16 16 NUM cana-572 231 18 features feature NOUN cana-572 231 19 . . PUNCT cana-572 232 1 6 6 X cana-572 232 2 . . X cana-572 232 3 conclusion conclusion NOUN cana-572 232 4 this this DET cana-572 232 5 research research NOUN cana-572 232 6 work work NOUN cana-572 232 7 provides provide VERB cana-572 232 8 valuable valuable ADJ cana-572 232 9 insights insight NOUN cana-572 232 10 by by ADP cana-572 232 11 utilizing utilize VERB cana-572 232 12 various various ADJ cana-572 232 13 machine machine NOUN cana-572 232 14 learning learning NOUN cana-572 232 15 and and CCONJ cana-572 232 16 feature feature NOUN cana-572 232 17 selection selection NOUN cana-572 232 18 techniques technique NOUN cana-572 232 19 in in ADP cana-572 232 20 the the DET cana-572 232 21 application application NOUN cana-572 232 22 of of ADP cana-572 232 23 breast breast NOUN cana-572 232 24 cancer cancer NOUN cana-572 232 25 prediction prediction NOUN cana-572 232 26 and and CCONJ cana-572 232 27 exploring explore VERB cana-572 232 28 various various ADJ cana-572 232 29 supervised supervised ADJ cana-572 232 30 learning learning NOUN cana-572 232 31 methods method NOUN cana-572 232 32 , , PUNCT cana-572 232 33 including include VERB cana-572 232 34 logistic logistic ADJ cana-572 232 35 regression regression NOUN cana-572 232 36 , , PUNCT cana-572 232 37 svm svm PROPN cana-572 232 38 , , PUNCT cana-572 232 39 knn knn PROPN cana-572 232 40 , , PUNCT cana-572 232 41 random random ADJ cana-572 232 42 forests forest NOUN cana-572 232 43 , , PUNCT cana-572 232 44 and and CCONJ cana-572 232 45 ann ann PROPN cana-572 232 46 . . PUNCT cana-572 233 1 the the DET cana-572 233 2 choice choice NOUN cana-572 233 3 of of ADP cana-572 233 4 feature feature NOUN cana-572 233 5 selection selection NOUN cana-572 233 6 method method NOUN cana-572 233 7 , , PUNCT cana-572 233 8 such such ADJ cana-572 233 9 as as ADP cana-572 233 10 pso pso NOUN cana-572 233 11 , , PUNCT cana-572 233 12 gwo gwo PROPN cana-572 233 13 , , PUNCT cana-572 233 14 or or CCONJ cana-572 233 15 a a DET cana-572 233 16 hybrid hybrid ADJ cana-572 233 17 pso pso NOUN cana-572 233 18 - - PUNCT cana-572 233 19 gwo gwo NOUN cana-572 233 20 approach approach NOUN cana-572 233 21 , , PUNCT cana-572 233 22 significantly significantly ADV cana-572 233 23 influenced influence VERB cana-572 233 24 the the DET cana-572 233 25 performance performance NOUN cana-572 233 26 of of ADP cana-572 233 27 the the DET cana-572 233 28 classifiers classifier NOUN cana-572 233 29 . . PUNCT cana-572 234 1 these these DET cana-572 234 2 optimization optimization NOUN cana-572 234 3 algorithms algorithm NOUN cana-572 234 4 helped helped AUX cana-572 234 5 identify identify VERB cana-572 234 6 the the DET cana-572 234 7 most most ADV cana-572 234 8 relevant relevant ADJ cana-572 234 9 features feature NOUN cana-572 234 10 from from ADP cana-572 234 11 the the DET cana-572 234 12 dataset dataset NOUN cana-572 234 13 , , PUNCT cana-572 234 14 improving improve VERB cana-572 234 15 the the DET cana-572 234 16 efficiency efficiency NOUN cana-572 234 17 and and CCONJ cana-572 234 18 effectiveness effectiveness NOUN cana-572 234 19 of of ADP cana-572 234 20 our our PRON cana-572 234 21 predictive predictive ADJ cana-572 234 22 models model NOUN cana-572 234 23 . . PUNCT cana-572 235 1 furthermore furthermore ADV cana-572 235 2 , , PUNCT cana-572 235 3 our our PRON cana-572 235 4 study study NOUN cana-572 235 5 demonstrated demonstrate VERB cana-572 235 6 the the DET cana-572 235 7 effectiveness effectiveness NOUN cana-572 235 8 of of ADP cana-572 235 9 different different ADJ cana-572 235 10 classifiers classifier NOUN cana-572 235 11 in in ADP cana-572 235 12 predicting predict VERB cana-572 235 13 breast breast NOUN cana-572 235 14 cancer cancer NOUN cana-572 235 15 outcomes outcome NOUN cana-572 235 16 . . PUNCT cana-572 236 1 svm svm PROPN cana-572 236 2 showed show VERB cana-572 236 3 promise promise NOUN cana-572 236 4 in in ADP cana-572 236 5 handling handle VERB cana-572 236 6 high high ADJ cana-572 236 7 - - PUNCT cana-572 236 8 dimensional dimensional ADJ cana-572 236 9 data datum NOUN cana-572 236 10 and and CCONJ cana-572 236 11 finding find VERB cana-572 236 12 optimal optimal ADJ cana-572 236 13 hyperplanes hyperplane NOUN cana-572 236 14 for for ADP cana-572 236 15 classification classification NOUN cana-572 236 16 . . PUNCT cana-572 237 1 lr lr INTJ cana-572 237 2 , , PUNCT cana-572 237 3 knn knn PROPN cana-572 237 4 , , PUNCT cana-572 237 5 and and CCONJ cana-572 237 6 rf rf PRON cana-572 237 7 also also ADV cana-572 237 8 performed perform VERB cana-572 237 9 well well ADV cana-572 237 10 , , PUNCT cana-572 237 11 each each PRON cana-572 237 12 offering offer VERB cana-572 237 13 unique unique ADJ cana-572 237 14 advantages advantage NOUN cana-572 237 15 in in ADP cana-572 237 16 terms term NOUN cana-572 237 17 of of ADP cana-572 237 18 simplicity simplicity NOUN cana-572 237 19 , , PUNCT cana-572 237 20 interpretability interpretability NOUN cana-572 237 21 , , PUNCT cana-572 237 22 and and CCONJ cana-572 237 23 ability ability NOUN cana-572 237 24 to to PART cana-572 237 25 handle handle VERB cana-572 237 26 nonlinear nonlinear ADJ cana-572 237 27 relationships relationship NOUN cana-572 237 28 in in ADP cana-572 237 29 the the DET cana-572 237 30 data datum NOUN cana-572 237 31 . . PUNCT cana-572 238 1 performance performance NOUN cana-572 238 2 evaluation evaluation NOUN cana-572 238 3 using use VERB cana-572 238 4 metrics metric NOUN cana-572 238 5 such such ADJ cana-572 238 6 as as ADP cana-572 238 7 accuracy accuracy NOUN cana-572 238 8 , , PUNCT cana-572 238 9 precision precision NOUN cana-572 238 10 , , PUNCT cana-572 238 11 recall recall NOUN cana-572 238 12 ( ( PUNCT cana-572 238 13 sensitivity sensitivity NOUN cana-572 238 14 ) ) PUNCT cana-572 238 15 , , PUNCT cana-572 238 16 and and CCONJ cana-572 238 17 specificity specificity NOUN cana-572 238 18 provided provide VERB cana-572 238 19 a a DET cana-572 238 20 comprehensive comprehensive ADJ cana-572 238 21 assessment assessment NOUN cana-572 238 22 of of ADP cana-572 238 23 the the DET cana-572 238 24 models model NOUN cana-572 238 25 ' ' PART cana-572 238 26 predictive predictive ADJ cana-572 238 27 capabilities capability NOUN cana-572 238 28 . . PUNCT cana-572 239 1 our our PRON cana-572 239 2 findings finding NOUN cana-572 239 3 underscore underscore VERB cana-572 239 4 the the DET cana-572 239 5 potential potential NOUN cana-572 239 6 of of ADP cana-572 239 7 machine machine NOUN cana-572 239 8 learning learn VERB cana-572 239 9 for for ADP cana-572 239 10 improving improve VERB cana-572 239 11 breast breast NOUN cana-572 239 12 cancer cancer NOUN cana-572 239 13 diagnosis diagnosis NOUN cana-572 239 14 and and CCONJ cana-572 239 15 treatment treatment NOUN cana-572 239 16 . . PUNCT cana-572 240 1 by by ADP cana-572 240 2 leveraging leverage VERB cana-572 240 3 advanced advanced ADJ cana-572 240 4 computational computational ADJ cana-572 240 5 techniques technique NOUN cana-572 240 6 and and CCONJ cana-572 240 7 optimization optimization NOUN cana-572 240 8 algorithms algorithm NOUN cana-572 240 9 , , PUNCT cana-572 240 10 we we PRON cana-572 240 11 can can AUX cana-572 240 12 enhance enhance VERB cana-572 240 13 the the DET cana-572 240 14 accuracy accuracy NOUN cana-572 240 15 and and CCONJ cana-572 240 16 efficiency efficiency NOUN cana-572 240 17 of of ADP cana-572 240 18 breast breast NOUN cana-572 240 19 cancer cancer NOUN cana-572 240 20 diagnostic diagnostic ADJ cana-572 240 21 systems system NOUN cana-572 240 22 , , PUNCT cana-572 240 23 ultimately ultimately ADV cana-572 240 24 leading lead VERB cana-572 240 25 to to ADP cana-572 240 26 improved improve VERB cana-572 240 27 patient patient ADJ cana-572 240 28 care care NOUN cana-572 240 29 and and CCONJ cana-572 240 30 outcomes outcome NOUN cana-572 240 31 in in ADP cana-572 240 32 the the DET cana-572 240 33 fight fight NOUN cana-572 240 34 against against ADP cana-572 240 35 this this DET cana-572 240 36 debilitating debilitate VERB cana-572 240 37 disease disease NOUN cana-572 240 38 . . PUNCT cana-572 241 1 references reference NOUN cana-572 241 2 [ [ X cana-572 241 3 1 1 NUM cana-572 241 4 ] ] X cana-572 241 5 sung sung PROPN cana-572 241 6 , , PUNCT cana-572 241 7 h. h. PROPN cana-572 241 8 ferlay ferlay PROPN cana-572 241 9 , , PUNCT cana-572 241 10 j. j. PROPN cana-572 241 11 siegel siegel PROPN cana-572 241 12 , , PUNCT cana-572 241 13 r.l r.l PROPN cana-572 241 14 . . PROPN cana-572 241 15 laversanne laversanne PROPN cana-572 241 16 , , PUNCT cana-572 241 17 m.soerjomataram m.soerjomataram PROPN cana-572 241 18 , , PUNCT cana-572 241 19 i. i. PROPN cana-572 241 20 jemal jemal PROPN cana-572 241 21 , , PUNCT cana-572 241 22 a. a. NOUN cana-572 241 23 ; ; PUNCT cana-572 241 24 bray bray PROPN cana-572 241 25 , , PUNCT cana-572 241 26 f. f. PROPN cana-572 241 27 global global PROPN cana-572 241 28 cancer cancer PROPN cana-572 241 29 statistics statistic NOUN cana-572 241 30 2020 2020 NUM cana-572 241 31 : : PUNCT cana-572 241 32 globocan globocan PROPN cana-572 241 33 estimates estimate NOUN cana-572 241 34 of of ADP cana-572 241 35 incidence incidence NOUN cana-572 241 36 and and CCONJ cana-572 241 37 mortality mortality NOUN cana-572 241 38 worldwide worldwide ADV cana-572 241 39 for for ADP cana-572 241 40 36 36 NUM cana-572 241 41 cancers cancer NOUN cana-572 241 42 in in ADP cana-572 241 43 185 185 NUM cana-572 241 44 countries country NOUN cana-572 241 45 . . PUNCT cana-572 242 1 ca can AUX cana-572 242 2 cancer cancer PROPN cana-572 242 3 j. j. PROPN cana-572 242 4 clin clin PROPN cana-572 242 5 . . PUNCT cana-572 243 1 2021 2021 NUM cana-572 243 2 , , PUNCT cana-572 243 3 71 71 NUM cana-572 243 4 , , PUNCT cana-572 243 5 209–249 209–249 NUM cana-572 243 6 . . PUNCT cana-572 244 1 [ [ X cana-572 244 2 2 2 NUM cana-572 244 3 ] ] PUNCT cana-572 244 4 world world NOUN cana-572 244 5 health health NOUN cana-572 244 6 organization organization NOUN cana-572 244 7 . . PUNCT cana-572 245 1 breast breast NOUN cana-572 245 2 cancer cancer NOUN cana-572 245 3 . . PUNCT cana-572 246 1 available available ADJ cana-572 246 2 online online ADV cana-572 246 3 : : PUNCT cana-572 246 4 https://www.who.int/news-room/factsheets/detail/breast-cancer https://www.who.int/news-room/factsheets/detail/breast-cancer NOUN cana-572 246 5 ( ( PUNCT cana-572 246 6 accessed access VERB cana-572 246 7 on on ADP cana-572 246 8 19 19 NUM cana-572 246 9 july july PROPN cana-572 246 10 2021 2021 NUM cana-572 246 11 ) ) PUNCT cana-572 246 12 . . PUNCT cana-572 247 1 [ [ X cana-572 247 2 3 3 NUM cana-572 247 3 ] ] X cana-572 247 4 hamashima hamashima PROPN cana-572 247 5 , , PUNCT cana-572 247 6 c. c. PROPN cana-572 247 7 hattori hattori PROPN cana-572 247 8 , , PUNCT cana-572 247 9 m. m. NOUN cana-572 247 10 honjo honjo PROPN cana-572 247 11 , , PUNCT cana-572 247 12 s. s. PROPN cana-572 247 13 ; ; PUNCT cana-572 247 14 kasahara kasahara PROPN cana-572 247 15 , , PUNCT cana-572 247 16 y. y. PROPN cana-572 247 17 ; ; PUNCT cana-572 247 18 katayama katayama PROPN cana-572 247 19 , , PUNCT cana-572 247 20 t. t. PROPN cana-572 247 21 nakai nakai PROPN cana-572 247 22 , , PUNCT cana-572 247 23 m.nakayama m.nakayama PROPN cana-572 247 24 , , PUNCT cana-572 247 25 t. t. PROPN cana-572 247 26 morita morita PROPN cana-572 247 27 , , PUNCT cana-572 247 28 t. t. PROPN cana-572 247 29 ohta ohta PROPN cana-572 247 30 , , PUNCT cana-572 247 31 k. k. PROPN cana-572 247 32 ohnuki ohnuki PROPN cana-572 247 33 , , PUNCT cana-572 247 34 k.et k.et PROPN cana-572 247 35 al al PROPN cana-572 247 36 . . PUNCT cana-572 248 1 the the DET cana-572 248 2 japanese japanese ADJ cana-572 248 3 guidelines guideline NOUN cana-572 248 4 for for ADP cana-572 248 5 breast breast NOUN cana-572 248 6 cancer cancer NOUN cana-572 248 7 screening screening NOUN cana-572 248 8 . . PUNCT cana-572 249 1 jpn jpn PROPN cana-572 249 2 . . PUNCT cana-572 250 1 j. j. PROPN cana-572 250 2 clin clin PROPN cana-572 250 3 . . PUNCT cana-572 251 1 oncol oncol ADJ cana-572 251 2 . . PUNCT cana-572 252 1 2016 2016 NUM cana-572 252 2 , , PUNCT cana-572 252 3 46 46 NUM cana-572 252 4 , , PUNCT cana-572 252 5 482–492 482–492 NUM cana-572 252 6 . . PUNCT cana-572 253 1 communications communication NOUN cana-572 253 2 on on ADP cana-572 253 3 applied apply VERB cana-572 253 4 nonlinear nonlinear ADJ cana-572 253 5 analysis analysis NOUN cana-572 253 6 issn issn NOUN cana-572 253 7 : : PUNCT cana-572 253 8 1074 1074 NUM cana-572 253 9 - - PUNCT cana-572 253 10 133x 133x NUM cana-572 253 11 vol vol NOUN cana-572 253 12 31 31 NUM cana-572 253 13 no no NOUN cana-572 253 14 . . NOUN cana-572 253 15 2 2 NUM cana-572 253 16 ( ( PUNCT cana-572 253 17 2024 2024 NUM cana-572 253 18 ) ) PUNCT cana-572 253 19 350 350 NUM cana-572 253 20 https://internationalpubls.com https://internationalpubls.com X cana-572 254 1 [ [ X cana-572 254 2 4 4 NUM cana-572 254 3 ] ] X cana-572 254 4 duffy duffy PROPN cana-572 254 5 , , PUNCT cana-572 254 6 s.w s.w PROPN cana-572 254 7 . . PROPN cana-572 254 8 tabΓ‘r tabΓ‘r PROPN cana-572 254 9 , , PUNCT cana-572 254 10 l.yen l.yen NOUN cana-572 254 11 , , PUNCT cana-572 254 12 a.m.f a.m.f NOUN cana-572 254 13 . . PUNCT cana-572 255 1 dean dean PROPN cana-572 255 2 , , PUNCT cana-572 255 3 p.b p.b PROPN cana-572 255 4 . . PROPN cana-572 255 5 ; ; PUNCT cana-572 255 6 smith smith PROPN cana-572 255 7 , , PUNCT cana-572 255 8 r.a.jonsson r.a.jonsson PROPN cana-572 255 9 , , PUNCT cana-572 255 10 h.tΓΆrnberg h.tΓΆrnberg PROPN cana-572 255 11 , , PUNCT cana-572 255 12 s. s. PROPN cana-572 255 13 ; ; PUNCT cana-572 255 14 chen chen PROPN cana-572 255 15 , , PUNCT cana-572 255 16 s.l.s s.l.s ADJ cana-572 255 17 . . PUNCT cana-572 255 18 chiu chiu PROPN cana-572 255 19 , , PUNCT cana-572 255 20 s.y.h s.y.h PROPN cana-572 255 21 . . PROPN cana-572 255 22 fann fann PROPN cana-572 255 23 , , PUNCT cana-572 255 24 j.c.y j.c.y X cana-572 255 25 et et PROPN cana-572 255 26 al al PROPN cana-572 255 27 . . PROPN cana-572 255 28 mammography mammography NOUN cana-572 255 29 screening screening NOUN cana-572 255 30 reduces reduce VERB cana-572 255 31 rates rate NOUN cana-572 255 32 of of ADP cana-572 255 33 advanced advanced ADJ cana-572 255 34 and and CCONJ cana-572 255 35 fatal fatal ADJ cana-572 255 36 breast breast NOUN cana-572 255 37 cancers cancer NOUN cana-572 255 38 : : PUNCT cana-572 255 39 results result NOUN cana-572 255 40 in in ADP cana-572 255 41 549,091 549,091 NUM cana-572 255 42 women woman NOUN cana-572 255 43 . . PUNCT cana-572 256 1 cancer cancer NOUN cana-572 256 2 2020 2020 NUM cana-572 256 3 , , PUNCT cana-572 256 4 126 126 NUM cana-572 256 5 , , PUNCT cana-572 256 6 2971–2979 2971–2979 NUM cana-572 256 7 . . PUNCT cana-572 257 1 [ [ X cana-572 257 2 5 5 NUM cana-572 257 3 ] ] X cana-572 257 4 wang wang PROPN cana-572 257 5 , , PUNCT cana-572 257 6 l. l. PROPN cana-572 257 7 early early ADJ cana-572 257 8 diagnosis diagnosis NOUN cana-572 257 9 of of ADP cana-572 257 10 breast breast NOUN cana-572 257 11 cancer cancer NOUN cana-572 257 12 . . PUNCT cana-572 258 1 sensors sensor NOUN cana-572 258 2 2017 2017 NUM cana-572 258 3 , , PUNCT cana-572 258 4 17 17 NUM cana-572 258 5 , , PUNCT cana-572 258 6 157 157 NUM cana-572 258 7 [ [ SYM cana-572 258 8 6 6 NUM cana-572 258 9 ] ] X cana-572 258 10 gilbert gilbert PROPN cana-572 258 11 , , PUNCT cana-572 258 12 f.j f.j PROPN cana-572 258 13 . . PROPN cana-572 258 14 pinker pinker NOUN cana-572 258 15 - - PUNCT cana-572 258 16 domening domening NOUN cana-572 258 17 , , PUNCT cana-572 258 18 k. k. NOUN cana-572 258 19 diagnosis diagnosis NOUN cana-572 258 20 and and CCONJ cana-572 258 21 staging staging NOUN cana-572 258 22 of of ADP cana-572 258 23 breast breast NOUN cana-572 258 24 cancer cancer NOUN cana-572 258 25 : : PUNCT cana-572 258 26 when when SCONJ cana-572 258 27 and and CCONJ cana-572 258 28 how how SCONJ cana-572 258 29 to to PART cana-572 258 30 use use VERB cana-572 258 31 mammography mammography NOUN cana-572 258 32 , , PUNCT cana-572 258 33 tomosynthesis tomosynthesis NOUN cana-572 258 34 , , PUNCT cana-572 258 35 ultrasound ultrasound NOUN cana-572 258 36 , , PUNCT cana-572 258 37 contrast contrast NOUN cana-572 258 38 - - PUNCT cana-572 258 39 enhanced enhance VERB cana-572 258 40 mammography mammography NOUN cana-572 258 41 , , PUNCT cana-572 258 42 and and CCONJ cana-572 258 43 magnetic magnetic ADJ cana-572 258 44 resonance resonance NOUN cana-572 258 45 imaging imaging NOUN cana-572 258 46 . . PUNCT cana-572 259 1 2019 2019 NUM cana-572 259 2 ; ; PUNCT cana-572 259 3 pp pp ADP cana-572 259 4 . . PUNCT cana-572 260 1 155–166 155–166 NUM cana-572 260 2 . . PUNCT cana-572 261 1 isbn isbn PROPN cana-572 261 2 9783030111496 9783030111496 NUM cana-572 261 3 . . PUNCT cana-572 262 1 [ [ X cana-572 262 2 7 7 NUM cana-572 262 3 ] ] SYM cana-572 262 4 hofvind hofvind NOUN cana-572 262 5 , , PUNCT cana-572 262 6 s. s. PROPN cana-572 262 7 holen holen PROPN cana-572 262 8 , , PUNCT cana-572 262 9 Γ₯.s Γ₯.s PROPN cana-572 262 10 . . PROPN cana-572 262 11 aase aase PROPN cana-572 262 12 , , PUNCT cana-572 262 13 h.s.houssami h.s.houssami PROPN cana-572 262 14 , , PUNCT cana-572 262 15 n. n. NOUN cana-572 262 16 sebuΓΈdegΓ₯rd sebuΓΈdegΓ₯rd NOUN cana-572 262 17 , , PUNCT cana-572 262 18 s.moger s.moger ADJ cana-572 262 19 , , PUNCT cana-572 262 20 t.a.;haldorsen t.a.;haldorsen NUM cana-572 262 21 , , PUNCT cana-572 262 22 i.s i.s PROPN cana-572 262 23 . . PROPN cana-572 262 24 akslen akslen PROPN cana-572 262 25 , , PUNCT cana-572 262 26 l.a l.a PROPN cana-572 262 27 . . PROPN cana-572 262 28 two two NUM cana-572 262 29 - - PUNCT cana-572 262 30 view view NOUN cana-572 262 31 digital digital ADJ cana-572 262 32 breast breast NOUN cana-572 262 33 tomosynthesis tomosynthesis NOUN cana-572 262 34 versus versus ADP cana-572 262 35 digital digital ADJ cana-572 262 36 mammography mammography NOUN cana-572 262 37 in in ADP cana-572 262 38 a a DET cana-572 262 39 population population NOUN cana-572 262 40 - - PUNCT cana-572 262 41 based base VERB cana-572 262 42 breast breast NOUN cana-572 262 43 cancer cancer NOUN cana-572 262 44 screening screen VERB cana-572 262 45 programme programme NOUN cana-572 262 46 ( ( PUNCT cana-572 262 47 to to PART cana-572 262 48 - - PUNCT cana-572 262 49 be be AUX cana-572 262 50 ): ): PUNCT cana-572 262 51 a a DET cana-572 262 52 randomised randomise VERB cana-572 262 53 , , PUNCT cana-572 262 54 controlled control VERB cana-572 262 55 trial trial NOUN cana-572 262 56 . . PUNCT cana-572 263 1 lancet lancet PROPN cana-572 263 2 oncol oncol PROPN cana-572 263 3 . . PUNCT cana-572 264 1 2019 2019 NUM cana-572 264 2 , , PUNCT cana-572 264 3 20 20 NUM cana-572 264 4 , , PUNCT cana-572 264 5 795–805 795–805 NUM cana-572 264 6 . . PUNCT cana-572 265 1 [ [ X cana-572 265 2 8 8 NUM cana-572 265 3 ] ] PUNCT cana-572 265 4 . . PUNCT cana-572 266 1 ahuja ahuja PROPN cana-572 266 2 , , PUNCT cana-572 266 3 a.s a.s PROPN cana-572 266 4 . . PROPN cana-572 267 1 the the DET cana-572 267 2 impact impact NOUN cana-572 267 3 of of ADP cana-572 267 4 artificial artificial ADJ cana-572 267 5 intelligence intelligence NOUN cana-572 267 6 in in ADP cana-572 267 7 medicine medicine NOUN cana-572 267 8 on on ADP cana-572 267 9 the the DET cana-572 267 10 future future ADJ cana-572 267 11 role role NOUN cana-572 267 12 of of ADP cana-572 267 13 the the DET cana-572 267 14 physician physician NOUN cana-572 267 15 . . PUNCT cana-572 268 1 peer peer NOUN cana-572 268 2 j j PROPN cana-572 268 3 2019 2019 NUM cana-572 268 4 , , PUNCT cana-572 268 5 7 7 NUM cana-572 268 6 , , PUNCT cana-572 268 7 e7702 e7702 NOUN cana-572 268 8 . . PUNCT cana-572 269 1 [ [ X cana-572 269 2 9 9 NUM cana-572 269 3 ] ] X cana-572 269 4 abdullah abdullah PROPN cana-572 269 5 , , PUNCT cana-572 269 6 r. r. PROPN cana-572 269 7 fakieh fakieh PROPN cana-572 269 8 , , PUNCT cana-572 269 9 b. b. PROPN cana-572 269 10 health health PROPN cana-572 269 11 care care PROPN cana-572 269 12 employees employee NOUN cana-572 269 13 ’ ’ PART cana-572 269 14 perceptions perception NOUN cana-572 269 15 of of ADP cana-572 269 16 the the DET cana-572 269 17 use use NOUN cana-572 269 18 of of ADP cana-572 269 19 artificial artificial ADJ cana-572 269 20 intelligence intelligence NOUN cana-572 269 21 applications application NOUN cana-572 269 22 : : PUNCT cana-572 269 23 survey survey NOUN cana-572 269 24 study study NOUN cana-572 269 25 . . PUNCT cana-572 270 1 j. j. PROPN cana-572 270 2 med med PROPN cana-572 270 3 . . PUNCT cana-572 270 4 internet internet NOUN cana-572 270 5 res re NOUN cana-572 270 6 . . PUNCT cana-572 270 7 2020 2020 NUM cana-572 270 8 , , PUNCT cana-572 270 9 22 22 NUM cana-572 270 10 , , PUNCT cana-572 270 11 1–8 1–8 NUM cana-572 270 12 . . PUNCT cana-572 271 1 [ [ X cana-572 271 2 10 10 NUM cana-572 271 3 ] ] SYM cana-572 271 4 doraiswamy doraiswamy ADJ cana-572 271 5 , , PUNCT cana-572 271 6 p.m. p.m. NOUN cana-572 271 7 blease blease ADJ cana-572 271 8 , , PUNCT cana-572 271 9 c.bodner c.bodner NOUN cana-572 271 10 , , PUNCT cana-572 271 11 k. k. PROPN cana-572 271 12 artificial artificial ADJ cana-572 271 13 intelligence intelligence NOUN cana-572 271 14 and and CCONJ cana-572 271 15 the the DET cana-572 271 16 future future NOUN cana-572 271 17 of of ADP cana-572 271 18 psychiatry psychiatry NOUN cana-572 271 19 : : PUNCT cana-572 271 20 insights insight NOUN cana-572 271 21 from from ADP cana-572 271 22 a a DET cana-572 271 23 global global ADJ cana-572 271 24 physician physician NOUN cana-572 271 25 survey survey NOUN cana-572 271 26 . . PUNCT cana-572 272 1 artif artif INTJ cana-572 272 2 . . PUNCT cana-572 273 1 intell intell PROPN cana-572 273 2 . . PUNCT cana-572 274 1 med med PROPN cana-572 274 2 . . PUNCT cana-572 275 1 2020 2020 NUM cana-572 275 2 , , PUNCT cana-572 275 3 102 102 NUM cana-572 275 4 , , PUNCT cana-572 275 5 101753 101753 NUM cana-572 275 6 . . PUNCT cana-572 276 1 [ [ X cana-572 276 2 11 11 NUM cana-572 276 3 ] ] PUNCT cana-572 276 4 . . PUNCT cana-572 277 1 blease blease PROPN cana-572 277 2 , , PUNCT cana-572 277 3 c. c. PROPN cana-572 277 4 kaptchuk kaptchuk PROPN cana-572 277 5 , , PUNCT cana-572 277 6 t.j.bernstein t.j.bernstein ADJ cana-572 277 7 , , PUNCT cana-572 277 8 m.h m.h PROPN cana-572 277 9 . . PROPN cana-572 277 10 mandl mandl PROPN cana-572 277 11 , , PUNCT cana-572 277 12 k.d k.d PROPN cana-572 277 13 . . PROPN cana-572 277 14 halamka halamka PROPN cana-572 277 15 , , PUNCT cana-572 277 16 j.d j.d PROPN cana-572 277 17 . . PROPN cana-572 277 18 desroches desroche NOUN cana-572 277 19 , , PUNCT cana-572 277 20 c.m c.m PROPN cana-572 277 21 . . PROPN cana-572 277 22 artificial artificial ADJ cana-572 277 23 intelligence intelligence NOUN cana-572 277 24 and and CCONJ cana-572 277 25 the the DET cana-572 277 26 future future NOUN cana-572 277 27 of of ADP cana-572 277 28 primary primary ADJ cana-572 277 29 care care NOUN cana-572 277 30 : : PUNCT cana-572 277 31 exploratory exploratory ADJ cana-572 277 32 qualitative qualitative ADJ cana-572 277 33 study study NOUN cana-572 277 34 of of ADP cana-572 277 35 uk uk PROPN cana-572 277 36 general general ADJ cana-572 277 37 practitioners practitioner NOUN cana-572 277 38 ’ ' PUNCT cana-572 277 39 views view NOUN cana-572 277 40 . . PUNCT cana-572 278 1 j. j. PROPN cana-572 278 2 med med PROPN cana-572 278 3 . . PUNCT cana-572 278 4 internet internet NOUN cana-572 278 5 res re NOUN cana-572 278 6 . . PROPN cana-572 278 7 2019 2019 NUM cana-572 278 8 , , PUNCT cana-572 278 9 21 21 NUM cana-572 278 10 , , PUNCT cana-572 278 11 1–10 1–10 NOUN cana-572 278 12 . . PUNCT cana-572 279 1 [ [ X cana-572 279 2 12 12 NUM cana-572 279 3 ] ] X cana-572 279 4 meskΓ³ meskΓ³ PROPN cana-572 279 5 , , PUNCT cana-572 279 6 b. b. PROPN cana-572 279 7 gΓΆrΓΆg gΓΆrΓΆg PROPN cana-572 279 8 , , PUNCT cana-572 279 9 m. m. NOUN cana-572 279 10 a a DET cana-572 279 11 short short ADJ cana-572 279 12 guide guide NOUN cana-572 279 13 for for ADP cana-572 279 14 medical medical ADJ cana-572 279 15 professionals professional NOUN cana-572 279 16 in in ADP cana-572 279 17 the the DET cana-572 279 18 era era NOUN cana-572 279 19 of of ADP cana-572 279 20 artificial artificial ADJ cana-572 279 21 intelligence intelligence NOUN cana-572 279 22 . . PUNCT cana-572 280 1 npj npj NOUN cana-572 280 2 digit digit PROPN cana-572 280 3 . . PUNCT cana-572 281 1 med med PROPN cana-572 281 2 . . PUNCT cana-572 282 1 2020 2020 NUM cana-572 282 2 , , PUNCT cana-572 282 3 3 3 NUM cana-572 282 4 , , PUNCT cana-572 282 5 126 126 NUM cana-572 282 6 . . PUNCT cana-572 283 1 [ [ X cana-572 283 2 13 13 NUM cana-572 283 3 ] ] X cana-572 283 4 kelly kelly PROPN cana-572 283 5 , , PUNCT cana-572 283 6 c.j c.j PROPN cana-572 283 7 . . PROPN cana-572 283 8 karthikesalingam karthikesalingam ADJ cana-572 283 9 , , PUNCT cana-572 283 10 a.suleyman a.suleyman NOUN cana-572 283 11 , , PUNCT cana-572 283 12 m. m. NOUN cana-572 283 13 corrado corrado PROPN cana-572 283 14 , , PUNCT cana-572 283 15 g. g. PROPN cana-572 283 16 king king PROPN cana-572 283 17 , , PUNCT cana-572 283 18 d. d. PROPN cana-572 283 19 key key NOUN cana-572 283 20 challenges challenge NOUN cana-572 283 21 for for ADP cana-572 283 22 delivering deliver VERB cana-572 283 23 clinical clinical ADJ cana-572 283 24 impact impact NOUN cana-572 283 25 with with ADP cana-572 283 26 artificial artificial ADJ cana-572 283 27 intelligence intelligence NOUN cana-572 283 28 . . PUNCT cana-572 284 1 bmc bmc PROPN cana-572 284 2 med med PROPN cana-572 284 3 . . PROPN cana-572 285 1 2019 2019 NUM cana-572 285 2 , , PUNCT cana-572 285 3 17 17 NUM cana-572 285 4 , , PUNCT cana-572 285 5 195 195 NUM cana-572 285 6 . . PUNCT cana-572 286 1 [ [ X cana-572 286 2 14 14 NUM cana-572 286 3 ] ] X cana-572 286 4 asan asan ADJ cana-572 286 5 , , PUNCT cana-572 286 6 o. o. PROPN cana-572 286 7 bayrak bayrak PROPN cana-572 286 8 , , PUNCT cana-572 286 9 a.e a.e PROPN cana-572 286 10 . . PROPN cana-572 286 11 choudhury choudhury PROPN cana-572 286 12 , , PUNCT cana-572 286 13 a. a. PROPN cana-572 286 14 artificial artificial ADJ cana-572 286 15 intelligence intelligence PROPN cana-572 286 16 and and CCONJ cana-572 286 17 human human NOUN cana-572 286 18 trust trust NOUN cana-572 286 19 in in ADP cana-572 286 20 healthcare healthcare PROPN cana-572 286 21 : : PUNCT cana-572 286 22 focus focus VERB cana-572 286 23 on on ADP cana-572 286 24 clinicians clinician NOUN cana-572 286 25 . . PUNCT cana-572 287 1 j. j. PROPN cana-572 287 2 med med PROPN cana-572 287 3 . . PUNCT cana-572 287 4 internet internet NOUN cana-572 287 5 res re NOUN cana-572 287 6 . . PUNCT cana-572 287 7 2020 2020 NUM cana-572 287 8 , , PUNCT cana-572 287 9 22 22 NUM cana-572 287 10 , , PUNCT cana-572 287 11 1–7 1–7 X cana-572 287 12 . . PUNCT cana-572 288 1 [ [ X cana-572 288 2 15 15 NUM cana-572 288 3 ] ] X cana-572 288 4 sadoughi sadoughi PROPN cana-572 288 5 , , PUNCT cana-572 288 6 f. f. PROPN cana-572 288 7 kazemy kazemy PROPN cana-572 288 8 , , PUNCT cana-572 288 9 z. z. PROPN cana-572 288 10 hamedan hamedan PROPN cana-572 288 11 , , PUNCT cana-572 288 12 f. f. PROPN cana-572 288 13 owji owji PROPN cana-572 288 14 , , PUNCT cana-572 288 15 l. l. PROPN cana-572 288 16 rahmanikatigari rahmanikatigari PROPN cana-572 288 17 , , PUNCT cana-572 288 18 m. m. NOUN cana-572 288 19 azadboni azadboni PROPN cana-572 288 20 , , PUNCT cana-572 288 21 t.t t.t PROPN cana-572 288 22 . . PROPN cana-572 288 23 artificial artificial ADJ cana-572 288 24 intelligence intelligence NOUN cana-572 288 25 methods method NOUN cana-572 288 26 for for ADP cana-572 288 27 the the DET cana-572 288 28 diagnosis diagnosis NOUN cana-572 288 29 of of ADP cana-572 288 30 breast breast NOUN cana-572 288 31 cancer cancer NOUN cana-572 288 32 by by ADP cana-572 288 33 image image NOUN cana-572 288 34 processing processing NOUN cana-572 288 35 : : PUNCT cana-572 288 36 a a DET cana-572 288 37 review review NOUN cana-572 288 38 . . PUNCT cana-572 289 1 breast breast NOUN cana-572 289 2 cancer cancer NOUN cana-572 289 3 2018 2018 NUM cana-572 289 4 , , PUNCT cana-572 289 5 10 10 NUM cana-572 289 6 , , PUNCT cana-572 289 7 219 219 NUM cana-572 289 8 – – PUNCT cana-572 289 9 230 230 NUM cana-572 289 10 . . PUNCT cana-572 290 1 [ [ X cana-572 290 2 16 16 NUM cana-572 290 3 ] ] X cana-572 290 4 abreu abreu PROPN cana-572 290 5 , , PUNCT cana-572 290 6 p.h p.h PROPN cana-572 290 7 . . PROPN cana-572 290 8 santos santos PROPN cana-572 290 9 , , PUNCT cana-572 290 10 m.s.abreu m.s.abreu PROPN cana-572 290 11 , , PUNCT cana-572 290 12 m.h m.h PROPN cana-572 290 13 . . PROPN cana-572 290 14 andrade andrade PROPN cana-572 290 15 , , PUNCT cana-572 290 16 b. b. PROPN cana-572 290 17 silva silva PROPN cana-572 290 18 , , PUNCT cana-572 290 19 d.c d.c PROPN cana-572 290 20 . . PROPN cana-572 290 21 predicting predict VERB cana-572 290 22 breast breast NOUN cana-572 290 23 cancer cancer NOUN cana-572 290 24 recurrence recurrence NOUN cana-572 290 25 using use VERB cana-572 290 26 machine machine NOUN cana-572 290 27 learning learn VERB cana-572 290 28 techniques technique NOUN cana-572 290 29 : : PUNCT cana-572 290 30 a a DET cana-572 290 31 systematic systematic ADJ cana-572 290 32 review review NOUN cana-572 290 33 . . PUNCT cana-572 290 34 acm acm PROPN cana-572 290 35 comput comput NOUN cana-572 290 36 . . PUNCT cana-572 291 1 surv surv NOUN cana-572 291 2 . . PUNCT cana-572 292 1 2016 2016 NUM cana-572 292 2 , , PUNCT cana-572 292 3 49 49 NUM cana-572 292 4 , , PUNCT cana-572 292 5 1–40 1–40 NUM cana-572 292 6 . . PUNCT cana-572 293 1 [ [ X cana-572 293 2 17 17 NUM cana-572 293 3 ] ] SYM cana-572 293 4 li li PROPN cana-572 293 5 , , PUNCT cana-572 293 6 j. j. PROPN cana-572 293 7 zhou zhou PROPN cana-572 293 8 , , PUNCT cana-572 293 9 z.dong z.dong PROPN cana-572 293 10 , , PUNCT cana-572 293 11 j. j. PROPN cana-572 293 12 fu fu PROPN cana-572 293 13 , , PUNCT cana-572 293 14 y. y. PROPN cana-572 293 15 li li PROPN cana-572 293 16 , , PUNCT cana-572 293 17 y. y. PROPN cana-572 293 18 luan luan PROPN cana-572 293 19 , , PUNCT cana-572 293 20 z. z. PROPN cana-572 293 21 peng peng PROPN cana-572 293 22 , , PUNCT cana-572 293 23 x. x. NOUN cana-572 293 24 predicting predict VERB cana-572 293 25 breast breast NOUN cana-572 293 26 cancer cancer NOUN cana-572 293 27 5 5 NUM cana-572 293 28 - - PUNCT cana-572 293 29 year year NOUN cana-572 293 30 survival survival NOUN cana-572 293 31 using use VERB cana-572 293 32 machine machine NOUN cana-572 293 33 learning learning NOUN cana-572 293 34 : : PUNCT cana-572 293 35 a a DET cana-572 293 36 systematic systematic ADJ cana-572 293 37 review review NOUN cana-572 293 38 . . PUNCT cana-572 294 1 plos plos PROPN cana-572 294 2 one one NUM cana-572 294 3 2021 2021 NUM cana-572 294 4 , , PUNCT cana-572 294 5 16 16 NUM cana-572 294 6 , , PUNCT cana-572 294 7 1–23 1–23 NOUN cana-572 294 8 . . PUNCT cana-572 295 1 [ [ X cana-572 295 2 18 18 NUM cana-572 295 3 ] ] PUNCT cana-572 295 4 tabl tabl NOUN cana-572 295 5 , , PUNCT cana-572 295 6 a.a.alkhateeb a.a.alkhateeb NOUN cana-572 295 7 , , PUNCT cana-572 295 8 a.elmaraghy a.elmaraghy NOUN cana-572 295 9 , , PUNCT cana-572 295 10 w.rueda w.rueda ADJ cana-572 295 11 , , PUNCT cana-572 295 12 l.ngom l.ngom PROPN cana-572 295 13 , , PUNCT cana-572 295 14 a. a. NOUN cana-572 295 15 a a DET cana-572 295 16 machine machine NOUN cana-572 295 17 learning learn VERB cana-572 295 18 approach approach NOUN cana-572 295 19 for for ADP cana-572 295 20 identifying identify VERB cana-572 295 21 gene gene NOUN cana-572 295 22 biomarkers biomarker NOUN cana-572 295 23 guiding guide VERB cana-572 295 24 the the DET cana-572 295 25 treatment treatment NOUN cana-572 295 26 of of ADP cana-572 295 27 breast breast NOUN cana-572 295 28 cancer cancer NOUN cana-572 295 29 . . PUNCT cana-572 296 1 front front NOUN cana-572 296 2 . . PUNCT cana-572 297 1 genet genet NOUN cana-572 297 2 . . PUNCT cana-572 298 1 2019 2019 NUM cana-572 298 2 , , PUNCT cana-572 298 3 10 10 NUM cana-572 298 4 , , PUNCT cana-572 298 5 256 256 NUM cana-572 298 6 . . PUNCT cana-572 299 1 [ [ X cana-572 299 2 19 19 NUM cana-572 299 3 ] ] X cana-572 299 4 alaa alaa PROPN cana-572 299 5 , , PUNCT cana-572 299 6 a.m. a.m. PROPN cana-572 299 7 gurdasani gurdasani PROPN cana-572 299 8 , , PUNCT cana-572 299 9 d. d. PROPN cana-572 299 10 harris harris PROPN cana-572 299 11 , , PUNCT cana-572 299 12 a.l a.l PROPN cana-572 299 13 . . PROPN cana-572 299 14 rashbass rashbass PROPN cana-572 299 15 , , PUNCT cana-572 299 16 j.van j.van ADJ cana-572 299 17 der der ADJ cana-572 299 18 schaar schaar NOUN cana-572 299 19 , , PUNCT cana-572 299 20 m. m. NOUN cana-572 299 21 machine machine NOUN cana-572 299 22 learning learn VERB cana-572 299 23 to to PART cana-572 299 24 guide guide VERB cana-572 299 25 the the DET cana-572 299 26 use use NOUN cana-572 299 27 of of ADP cana-572 299 28 adjuvant adjuvant ADJ cana-572 299 29 therapies therapy NOUN cana-572 299 30 for for ADP cana-572 299 31 breast breast NOUN cana-572 299 32 cancer cancer NOUN cana-572 299 33 . . PUNCT cana-572 300 1 nat nat PROPN cana-572 300 2 . . PUNCT cana-572 301 1 mach mach PROPN cana-572 301 2 . . PUNCT cana-572 302 1 intell intell PROPN cana-572 302 2 . . PUNCT cana-572 303 1 2021 2021 NUM cana-572 303 2 , , PUNCT cana-572 303 3 3 3 NUM cana-572 303 4 , , PUNCT cana-572 303 5 716–726 716–726 NUM cana-572 303 6 . . PUNCT cana-572 304 1 [ [ X cana-572 304 2 20 20 NUM cana-572 304 3 ] ] PUNCT cana-572 304 4 l. l. PROPN cana-572 304 5 c c PROPN cana-572 304 6 meena;p meena;p X cana-572 304 7 . . PUNCT cana-572 305 1 m m VERB cana-572 305 2 joe joe PROPN cana-572 305 3 prathap;s prathap;s PROPN cana-572 305 4 sankara sankara PROPN cana-572 305 5 narayanan narayanan PROPN cana-572 305 6 ( ( PUNCT cana-572 305 7 2023 2023 NUM cana-572 305 8 ) ) PUNCT cana-572 305 9 detection detection NOUN cana-572 305 10 of of ADP cana-572 305 11 breast breast NOUN cana-572 305 12 cancer cancer NOUN cana-572 305 13 using use VERB cana-572 305 14 curvelet curvelet NOUN cana-572 305 15 transform transform NOUN cana-572 305 16 and and CCONJ cana-572 305 17 adaptive adaptive ADJ cana-572 305 18 particle particle NOUN cana-572 305 19 swarm swarm NOUN cana-572 305 20 optimization optimization NOUN cana-572 305 21 technique technique NOUN cana-572 305 22 2023 2023 NUM cana-572 305 23 12th 12th NOUN cana-572 305 24 international international ADJ cana-572 305 25 conference conference NOUN cana-572 305 26 on on ADP cana-572 305 27 advanced advanced ADJ cana-572 305 28 computing computing NOUN cana-572 305 29 ( ( PUNCT cana-572 305 30 icoac icoac NOUN cana-572 305 31 ) ) PUNCT cana-572 305 32 year year NOUN cana-572 305 33 : : PUNCT cana-572 305 34 2023 2023 NUM cana-572 305 35 [ [ X cana-572 305 36 21 21 NUM cana-572 305 37 ] ] X cana-572 305 38 nurhayati;fajar nurhayati;fajar PROPN cana-572 305 39 agustian;muhammad agustian;muhammad PROPN cana-572 305 40 dzil dzil PROPN cana-572 305 41 ikram ikram PROPN cana-572 305 42 lubis(2020 lubis(2020 NOUN cana-572 305 43 ) ) PUNCT cana-572 305 44 particle particle NOUN cana-572 305 45 swarm swarm NOUN cana-572 305 46 optimization optimization NOUN cana-572 305 47 feature feature NOUN cana-572 305 48 selection selection NOUN cana-572 305 49 for for ADP cana-572 305 50 breast breast NOUN cana-572 305 51 cancer cancer NOUN cana-572 305 52 prediction prediction NOUN cana-572 305 53 2020 2020 NUM cana-572 305 54 8th 8th ADJ cana-572 305 55 international international ADJ cana-572 305 56 conference conference NOUN cana-572 305 57 on on ADP cana-572 305 58 cyber cyber NOUN cana-572 306 1 and and CCONJ cana-572 306 2 it it PRON cana-572 306 3 service service NOUN cana-572 306 4 management management NOUN cana-572 306 5 ( ( PUNCT cana-572 306 6 citsm citsm NOUN cana-572 306 7 ) ) PUNCT cana-572 306 8 year year NOUN cana-572 306 9 : : PUNCT cana-572 306 10 2020 2020 NUM cana-572 307 1 [ [ X cana-572 307 2 22 22 NUM cana-572 307 3 ] ] PUNCT cana-572 307 4 sannasi sannasi NOUN cana-572 307 5 chakravarthy chakravarthy PROPN cana-572 307 6 s s PART cana-572 307 7 r;harikumar r;harikumar PROPN cana-572 307 8 rajaguru;sundaresan rajaguru;sundaresan PROPN cana-572 307 9 chidambaram chidambaram PROPN cana-572 307 10 ( ( PUNCT cana-572 307 11 2022 2022 NUM cana-572 307 12 ) ) PUNCT cana-572 307 13 processing processing NOUN cana-572 307 14 of of ADP cana-572 307 15 wisconsin wisconsin PROPN cana-572 307 16 breast breast PROPN cana-572 307 17 cancer cancer NOUN cana-572 307 18 data datum NOUN cana-572 307 19 using use VERB cana-572 307 20 ebola ebola PROPN cana-572 307 21 optimization optimization NOUN cana-572 307 22 algorithm algorithm NOUN cana-572 307 23 with with ADP cana-572 307 24 mixture mixture NOUN cana-572 307 25 kernel kernel NOUN cana-572 307 26 svm svm VERB cana-572 307 27 2022 2022 NUM cana-572 307 28 smart smart ADJ cana-572 307 29 technologies technology NOUN cana-572 307 30 , , PUNCT cana-572 307 31 communication communication NOUN cana-572 307 32 and and CCONJ cana-572 307 33 robotics robotic NOUN cana-572 307 34 ( ( PUNCT cana-572 307 35 stcr stcr PROPN cana-572 307 36 ) ) PUNCT cana-572 307 37 year year NOUN cana-572 307 38 : : PUNCT cana-572 307 39 2022 2022 NUM cana-572 307 40 communications communication NOUN cana-572 307 41 on on ADP cana-572 307 42 applied apply VERB cana-572 307 43 nonlinear nonlinear ADJ cana-572 307 44 analysis analysis NOUN cana-572 307 45 issn issn NOUN cana-572 307 46 : : PUNCT cana-572 307 47 1074 1074 NUM cana-572 307 48 - - PUNCT cana-572 307 49 133x 133x NUM cana-572 307 50 vol vol NOUN cana-572 307 51 31 31 NUM cana-572 307 52 no no NOUN cana-572 307 53 . . NOUN cana-572 307 54 2 2 NUM cana-572 307 55 ( ( PUNCT cana-572 307 56 2024 2024 NUM cana-572 307 57 ) ) PUNCT cana-572 307 58 351 351 NUM cana-572 307 59 https://internationalpubls.com https://internationalpubls.com X cana-572 308 1 [ [ X cana-572 308 2 23 23 NUM cana-572 308 3 ] ] PUNCT cana-572 308 4 harish harish X cana-572 308 5 h;bharathi h;bharathi X cana-572 308 6 d d X cana-572 308 7 s;pratibha s;pratibha NOUN cana-572 308 8 m;deeksha m;deeksha PROPN cana-572 308 9 holla;ashwini holla;ashwini PROPN cana-572 308 10 k k PROPN cana-572 308 11 b;keerthana b;keerthana PROPN cana-572 309 1 k k X cana-572 309 2 r r X cana-572 309 3 ( ( PUNCT cana-572 309 4 2022 2022 NUM cana-572 309 5 ) ) PUNCT cana-572 309 6 particle particle NOUN cana-572 309 7 swarm swarm NOUN cana-572 309 8 optimization optimization NOUN cana-572 309 9 for for ADP cana-572 309 10 predicting predict VERB cana-572 309 11 breast breast NOUN cana-572 309 12 cancer cancer NOUN cana-572 309 13 2022 2022 NUM cana-572 309 14 international international ADJ cana-572 309 15 conference conference NOUN cana-572 309 16 on on ADP cana-572 309 17 knowledge knowledge NOUN cana-572 309 18 engineering engineering NOUN cana-572 309 19 and and CCONJ cana-572 309 20 communication communication NOUN cana-572 309 21 systems system NOUN cana-572 309 22 ( ( PUNCT cana-572 309 23 ickes icke NOUN cana-572 309 24 ) ) PUNCT cana-572 309 25 year year NOUN cana-572 309 26 : : PUNCT cana-572 309 27 2022 2022 NUM cana-572 310 1 [ [ X cana-572 310 2 24 24 NUM cana-572 310 3 ] ] PUNCT cana-572 310 4 maryam maryam PROPN cana-572 310 5 momtahen;shadi momtahen;shadi PROPN cana-572 310 6 momtahen;ramani momtahen;ramani PROPN cana-572 310 7 remaseshan;farid remaseshan;farid PROPN cana-572 310 8 golnaraghi(2023 golnaraghi(2023 NOUN cana-572 310 9 ) ) PUNCT cana-572 310 10 early early ADJ cana-572 310 11 detection detection NOUN cana-572 310 12 of of ADP cana-572 310 13 breast breast NOUN cana-572 310 14 cancer cancer NOUN cana-572 310 15 using use VERB cana-572 310 16 diffuse diffuse ADJ cana-572 310 17 optical optical ADJ cana-572 310 18 probe probe NOUN cana-572 310 19 and and CCONJ cana-572 310 20 ensemble ensemble ADJ cana-572 310 21 learning learning NOUN cana-572 310 22 method method NOUN cana-572 310 23 2023 2023 NUM cana-572 310 24 ieee ieee NOUN cana-572 310 25 mtt mtt PROPN cana-572 310 26 - - PUNCT cana-572 310 27 s s PROPN cana-572 310 28 international international ADJ cana-572 310 29 conference conference NOUN cana-572 310 30 on on ADP cana-572 310 31 numerical numerical PROPN cana-572 310 32 electromagnetic electromagnetic PROPN cana-572 310 33 and and CCONJ cana-572 310 34 multiphysics multiphysic NOUN cana-572 310 35 modeling modeling NOUN cana-572 310 36 and and CCONJ cana-572 310 37 optimization optimization NOUN cana-572 310 38 ( ( PUNCT cana-572 310 39 nemo nemo PROPN cana-572 310 40 ) ) PUNCT cana-572 310 41 year year NOUN cana-572 310 42 : : PUNCT cana-572 310 43 2023 2023 NUM cana-572 310 44 [ [ X cana-572 310 45 25 25 NUM cana-572 310 46 ] ] X cana-572 310 47 divya divya PROPN cana-572 310 48 baskaran;kavitha baskaran;kavitha PROPN cana-572 310 49 arunachalam arunachalam PROPN cana-572 310 50 ( ( PUNCT cana-572 310 51 2020 2020 NUM cana-572 310 52 ) ) PUNCT cana-572 310 53 comparison comparison NOUN cana-572 310 54 of of ADP cana-572 310 55 two two NUM cana-572 310 56 global global ADJ cana-572 310 57 optimization optimization NOUN cana-572 310 58 techniques technique NOUN cana-572 310 59 for for ADP cana-572 310 60 hyperthermia hyperthermia NOUN cana-572 310 61 treatment treatment NOUN cana-572 310 62 planning planning NOUN cana-572 310 63 of of ADP cana-572 310 64 breast breast NOUN cana-572 310 65 cancer cancer NOUN cana-572 310 66 : : PUNCT cana-572 310 67 coupled couple VERB cana-572 310 68 electromagnetic electromagnetic ADJ cana-572 310 69 and and CCONJ cana-572 310 70 thermal thermal ADJ cana-572 310 71 simulation simulation NOUN cana-572 310 72 study study NOUN cana-572 310 73 2020 2020 NUM cana-572 310 74 ieee ieee NOUN cana-572 310 75 mtt mtt PROPN cana-572 310 76 - - PUNCT cana-572 310 77 s s PROPN cana-572 310 78 international international ADJ cana-572 310 79 microwave microwave NOUN cana-572 310 80 biomedical biomedical PROPN cana-572 310 81 conference conference NOUN cana-572 310 82 ( ( PUNCT cana-572 310 83 imbioc imbioc NOUN cana-572 310 84 ) ) PUNCT cana-572 310 85 year year NOUN cana-572 310 86 : : PUNCT cana-572 310 87 2020 2020 NUM cana-572 311 1 [ [ X cana-572 311 2 26 26 NUM cana-572 311 3 ] ] PUNCT cana-572 311 4 farhad farhad PROPN cana-572 311 5 imani;zihang imani;zihang PROPN cana-572 311 6 qiu;hui qiu;hui PROPN cana-572 311 7 yang yang PROPN cana-572 311 8 ( ( PUNCT cana-572 311 9 2020 2020 NUM cana-572 311 10 ) ) PUNCT cana-572 311 11 markov markov NOUN cana-572 311 12 decision decision NOUN cana-572 311 13 process process NOUN cana-572 311 14 modeling modeling NOUN cana-572 311 15 for for ADP cana-572 311 16 multi multi ADJ cana-572 311 17 - - ADJ cana-572 311 18 stage stage ADJ cana-572 311 19 optimization optimization NOUN cana-572 311 20 of of ADP cana-572 311 21 intervention intervention NOUN cana-572 311 22 and and CCONJ cana-572 311 23 treatment treatment NOUN cana-572 311 24 strategies strategy NOUN cana-572 311 25 in in ADP cana-572 311 26 breast breast NOUN cana-572 311 27 cancer cancer NOUN cana-572 311 28 2020 2020 NUM cana-572 311 29 42nd 42nd X cana-572 311 30 annual annual ADJ cana-572 311 31 international international ADJ cana-572 311 32 conference conference NOUN cana-572 311 33 of of ADP cana-572 311 34 the the DET cana-572 311 35 ieee ieee NOUN cana-572 311 36 engineering engineering NOUN cana-572 311 37 in in ADP cana-572 311 38 medicine medicine PROPN cana-572 311 39 & & CCONJ cana-572 311 40 biology biology NOUN cana-572 311 41 society society NOUN cana-572 311 42 ( ( PUNCT cana-572 311 43 embc embc NOUN cana-572 311 44 ) ) PUNCT cana-572 311 45 year year NOUN cana-572 311 46 : : PUNCT cana-572 311 47 2020 2020 NUM cana-572 311 48 [ [ X cana-572 311 49 27 27 NUM cana-572 311 50 ] ] X cana-572 311 51 k k PROPN cana-572 311 52 vilohit;bharanidharan vilohit;bharanidharan PROPN cana-572 311 53 n;harikumar n;harikumar PROPN cana-572 311 54 rajaguru rajaguru X cana-572 311 55 ( ( PUNCT cana-572 311 56 2022 2022 NUM cana-572 311 57 ) ) PUNCT cana-572 311 58 improvisation improvisation NOUN cana-572 311 59 of of ADP cana-572 311 60 decision decision NOUN cana-572 311 61 tree tree NOUN cana-572 311 62 classification classification NOUN cana-572 311 63 performance performance NOUN cana-572 311 64 in in ADP cana-572 311 65 breast breast NOUN cana-572 311 66 cancer cancer NOUN cana-572 311 67 diagnosis diagnosis NOUN cana-572 311 68 using use VERB cana-572 311 69 elephant elephant NOUN cana-572 311 70 herding herd VERB cana-572 311 71 optimization optimization NOUN cana-572 311 72 2022 2022 NUM cana-572 311 73 smart smart ADJ cana-572 311 74 technologies technology NOUN cana-572 311 75 , , PUNCT cana-572 311 76 communication communication NOUN cana-572 311 77 and and CCONJ cana-572 311 78 robotics robotic NOUN cana-572 311 79 ( ( PUNCT cana-572 311 80 stcr stcr PROPN cana-572 311 81 ) ) PUNCT cana-572 311 82 year year NOUN cana-572 311 83 : : PUNCT cana-572 311 84 2022 2022 NUM cana-572 312 1 [ [ X cana-572 312 2 28 28 NUM cana-572 312 3 ] ] PUNCT cana-572 312 4 suman suman NOUN cana-572 312 5 mitra;sriyankar mitra;sriyankar PROPN cana-572 312 6 acharyya acharyya PROPN cana-572 312 7 ( ( PUNCT cana-572 312 8 2023 2023 NUM cana-572 312 9 ) ) PUNCT cana-572 312 10 identification identification NOUN cana-572 312 11 of of ADP cana-572 312 12 disease disease NOUN cana-572 312 13 critical critical ADJ cana-572 312 14 genes gene NOUN cana-572 312 15 for for ADP cana-572 312 16 triple triple ADJ cana-572 312 17 negative negative ADJ cana-572 312 18 breast breast NOUN cana-572 312 19 cancer cancer NOUN cana-572 312 20 , , PUNCT cana-572 312 21 tnbc tnbc ADV cana-572 312 22 , , PUNCT cana-572 312 23 using use VERB cana-572 312 24 particle particle NOUN cana-572 312 25 swarm swarm NOUN cana-572 312 26 optimization optimization NOUN cana-572 312 27 , , PUNCT cana-572 312 28 pso pso NOUN cana-572 312 29 , , PUNCT cana-572 312 30 with with ADP cana-572 312 31 machine machine NOUN cana-572 312 32 learning learn VERB cana-572 312 33 2023 2023 NUM cana-572 312 34 fifth fifth ADJ cana-572 312 35 international international ADJ cana-572 312 36 conference conference NOUN cana-572 312 37 on on ADP cana-572 312 38 electrical electrical ADJ cana-572 312 39 , , PUNCT cana-572 312 40 computer computer NOUN cana-572 312 41 and and CCONJ cana-572 312 42 communication communication NOUN cana-572 312 43 technologies technology NOUN cana-572 312 44 ( ( PUNCT cana-572 312 45 icecct icecct NOUN cana-572 312 46 ) ) PUNCT cana-572 312 47 year year NOUN cana-572 312 48 : : PUNCT cana-572 312 49 2023 2023 NUM cana-572 312 50 [ [ X cana-572 312 51 29 29 NUM cana-572 312 52 ] ] X cana-572 312 53 abd abd PROPN cana-572 312 54 allah allah PROPN cana-572 312 55 aouragh;mohamed aouragh;mohamed PROPN cana-572 312 56 bahaj bahaj PROPN cana-572 312 57 ( ( PUNCT cana-572 312 58 2023 2023 NUM cana-572 312 59 ) ) PUNCT cana-572 312 60 advancing advance VERB cana-572 312 61 breast breast NOUN cana-572 312 62 cancer cancer NOUN cana-572 312 63 diagnosis diagnosis NOUN cana-572 312 64 with with ADP cana-572 312 65 machine machine NOUN cana-572 312 66 learning learning NOUN cana-572 312 67 : : PUNCT cana-572 312 68 exploring explore VERB cana-572 312 69 data datum NOUN cana-572 312 70 balancing balancing NOUN cana-572 312 71 , , PUNCT cana-572 312 72 feature feature NOUN cana-572 312 73 selection selection NOUN cana-572 312 74 , , PUNCT cana-572 312 75 and and CCONJ cana-572 312 76 bayesian bayesian NOUN cana-572 312 77 optimization optimization NOUN cana-572 312 78 2023 2023 NUM cana-572 312 79 ieee ieee NOUN cana-572 312 80 6th 6th ADJ cana-572 312 81 international international ADJ cana-572 312 82 conference conference NOUN cana-572 312 83 on on ADP cana-572 312 84 cloud cloud NOUN cana-572 312 85 computing computing NOUN cana-572 312 86 and and CCONJ cana-572 312 87 artificial artificial ADJ cana-572 312 88 intelligence intelligence NOUN cana-572 312 89 : : PUNCT cana-572 312 90 technologies technology NOUN cana-572 312 91 and and CCONJ cana-572 312 92 applications application NOUN cana-572 312 93 ( ( PUNCT cana-572 312 94 cloudtech cloudtech NOUN cana-572 312 95 ) ) PUNCT cana-572 312 96 year year NOUN cana-572 312 97 : : PUNCT cana-572 312 98 2023 2023 NUM cana-572 312 99 [ [ SYM cana-572 312 100 30 30 NUM cana-572 312 101 ] ] PUNCT cana-572 312 102 alaria alaria PROPN cana-572 312 103 , , PUNCT cana-572 312 104 s. s. PROPN cana-572 312 105 k. k. PROPN cana-572 313 1 " " PUNCT cana-572 313 2 a a PROPN cana-572 313 3 .. .. PUNCT cana-572 313 4 raj raj PROPN cana-572 313 5 , , PUNCT cana-572 313 6 v. v. PROPN cana-572 313 7 sharma sharma PROPN cana-572 313 8 , , PUNCT cana-572 313 9 and and CCONJ cana-572 313 10 v. v. ADP cana-572 313 11 kumar kumar PROPN cana-572 313 12 . . PUNCT cana-572 314 1 β€œsimulation β€œsimulation NOUN cana-572 314 2 and and CCONJ cana-572 314 3 analysis analysis NOUN cana-572 314 4 of of ADP cana-572 314 5 hand hand NOUN cana-572 314 6 gesture gesture NOUN cana-572 314 7 recognition recognition NOUN cana-572 314 8 for for ADP cana-572 314 9 indian indian ADJ cana-572 314 10 sign sign NOUN cana-572 314 11 language language NOUN cana-572 314 12 using use VERB cana-572 314 13 cnn cnn PROPN cana-572 314 14 ” " PUNCT cana-572 314 15 . . PUNCT cana-572 314 16 " " PUNCT cana-572 315 1 international international ADJ cana-572 315 2 journal journal NOUN cana-572 315 3 on on ADP cana-572 315 4 recent recent ADJ cana-572 315 5 and and CCONJ cana-572 315 6 innovation innovation NOUN cana-572 315 7 trends trend NOUN cana-572 315 8 in in ADP cana-572 315 9 computing computing NOUN cana-572 315 10 and and CCONJ cana-572 315 11 communication communication NOUN cana-572 315 12 10 10 NUM cana-572 315 13 , , PUNCT cana-572 315 14 no no INTJ cana-572 315 15 . . NOUN cana-572 315 16 4 4 NUM cana-572 315 17 ( ( PUNCT cana-572 315 18 2022 2022 NUM cana-572 315 19 ): ): PUNCT cana-572 315 20 10 10 NUM cana-572 315 21 - - SYM cana-572 315 22 14 14 NUM cana-572 315 23 . . PUNCT cana-572 316 1 [ [ X cana-572 316 2 31 31 NUM cana-572 316 3 ] ] PUNCT cana-572 316 4 ashwini ashwini PROPN cana-572 316 5 , , PUNCT cana-572 316 6 k. k. PROPN cana-572 316 7 , , PUNCT cana-572 316 8 raj raj PROPN cana-572 316 9 , , PUNCT cana-572 316 10 a. a. PROPN cana-572 316 11 , , PUNCT cana-572 316 12 & & CCONJ cana-572 316 13 gupta gupta PROPN cana-572 316 14 , , PUNCT cana-572 316 15 m. m. NOUN cana-572 316 16 ( ( PUNCT cana-572 316 17 2016 2016 NUM cana-572 316 18 , , PUNCT cana-572 316 19 december december PROPN cana-572 316 20 ) ) PUNCT cana-572 316 21 . . PUNCT cana-572 317 1 performance performance NOUN cana-572 317 2 assessment assessment NOUN cana-572 317 3 and and CCONJ cana-572 317 4 orientation orientation NOUN cana-572 317 5 optimization optimization NOUN cana-572 317 6 of of ADP cana-572 317 7 100 100 NUM cana-572 317 8 kwp kwp PROPN cana-572 317 9 grid grid NOUN cana-572 317 10 connected connect VERB cana-572 317 11 solar solar ADJ cana-572 317 12 pv pv NOUN cana-572 317 13 system system NOUN cana-572 317 14 in in ADP cana-572 317 15 indian indian ADJ cana-572 317 16 scenario scenario NOUN cana-572 317 17 . . PUNCT cana-572 318 1 in in ADP cana-572 318 2 2016 2016 NUM cana-572 318 3 international international ADJ cana-572 318 4 conference conference NOUN cana-572 318 5 on on ADP cana-572 318 6 recent recent ADJ cana-572 318 7 advances advance NOUN cana-572 318 8 and and CCONJ cana-572 318 9 innovations innovation NOUN cana-572 318 10 in in ADP cana-572 318 11 engineering engineering NOUN cana-572 318 12 ( ( PUNCT cana-572 318 13 icraie icraie PROPN cana-572 318 14 ) ) PUNCT cana-572 318 15 ( ( PUNCT cana-572 318 16 pp pp X cana-572 318 17 . . PUNCT cana-572 319 1 1 1 NUM cana-572 319 2 - - SYM cana-572 319 3 7 7 NUM cana-572 319 4 ) ) PUNCT cana-572 319 5 . . PUNCT cana-572 320 1 ieee ieee NOUN cana-572 320 2 . . PUNCT cana-572 321 1 [ [ X cana-572 321 2 32 32 NUM cana-572 321 3 ] ] SYM cana-572 321 4 alaria alaria PROPN cana-572 321 5 , , PUNCT cana-572 321 6 satish satish PROPN cana-572 321 7 kumar kumar PROPN cana-572 321 8 , , PUNCT cana-572 321 9 ashish ashish PROPN cana-572 321 10 raj raj PROPN cana-572 321 11 , , PUNCT cana-572 321 12 vivek vivek PROPN cana-572 321 13 sharma sharma PROPN cana-572 321 14 , , PUNCT cana-572 321 15 and and CCONJ cana-572 321 16 vijay vijay PROPN cana-572 321 17 kumar kumar PROPN cana-572 321 18 . . PUNCT cana-572 322 1 " " PUNCT cana-572 322 2 simulation simulation NOUN cana-572 322 3 and and CCONJ cana-572 322 4 analysis analysis NOUN cana-572 322 5 of of ADP cana-572 322 6 hand hand NOUN cana-572 322 7 gesture gesture NOUN cana-572 322 8 recognition recognition NOUN cana-572 322 9 for for ADP cana-572 322 10 indian indian ADJ cana-572 322 11 sign sign NOUN cana-572 322 12 language language NOUN cana-572 322 13 using use VERB cana-572 322 14 cnn cnn PROPN cana-572 322 15 . . PUNCT cana-572 322 16 " " PUNCT cana-572 323 1 international international ADJ cana-572 323 2 journal journal NOUN cana-572 323 3 on on ADP cana-572 323 4 recent recent ADJ cana-572 323 5 and and CCONJ cana-572 323 6 innovation innovation NOUN cana-572 323 7 trends trend NOUN cana-572 323 8 in in ADP cana-572 323 9 computing computing NOUN cana-572 323 10 and and CCONJ cana-572 323 11 communication communication NOUN cana-572 323 12 10 10 NUM cana-572 323 13 , , PUNCT cana-572 323 14 no no INTJ cana-572 323 15 . . NOUN cana-572 323 16 4 4 NUM cana-572 323 17 ( ( PUNCT cana-572 323 18 2022 2022 NUM cana-572 323 19 ): ): PUNCT cana-572 323 20 10 10 NUM cana-572 323 21 - - SYM cana-572 323 22 14 14 NUM cana-572 323 23 . . PUNCT cana-572 324 1 [ [ X cana-572 324 2 33 33 NUM cana-572 324 3 ] ] X cana-572 324 4 [ [ X cana-572 324 5 yogi yogi NOUN cana-572 324 6 , , PUNCT cana-572 324 7 jyoti jyoti PROPN cana-572 324 8 , , PUNCT cana-572 324 9 upendra upendra PROPN cana-572 324 10 singh singh PROPN cana-572 324 11 chauhan chauhan PROPN cana-572 324 12 , , PUNCT cana-572 324 13 ashish ashish PROPN cana-572 324 14 raj raj PROPN cana-572 324 15 , , PUNCT cana-572 324 16 manoj manoj PROPN cana-572 324 17 gupta gupta PROPN cana-572 324 18 , , PUNCT cana-572 324 19 and and CCONJ cana-572 324 20 simranjeet simranjeet VERB cana-572 324 21 singh singh PROPN cana-572 324 22 sudan sudan PROPN cana-572 324 23 . . PUNCT cana-572 325 1 " " PUNCT cana-572 325 2 modeling model VERB cana-572 325 3 simulation simulation NOUN cana-572 325 4 and and CCONJ cana-572 325 5 performance performance NOUN cana-572 325 6 analysis analysis NOUN cana-572 325 7 of of ADP cana-572 325 8 lightweight lightweight ADJ cana-572 325 9 cryptography cryptography NOUN cana-572 325 10 for for ADP cana-572 325 11 iot iot NOUN cana-572 325 12 - - PUNCT cana-572 325 13 security security NOUN cana-572 325 14 . . PUNCT cana-572 325 15 " " PUNCT cana-572 326 1 in in ADP cana-572 326 2 2018 2018 NUM cana-572 326 3 3rd 3rd ADJ cana-572 326 4 international international ADJ cana-572 326 5 conference conference NOUN cana-572 326 6 and and CCONJ cana-572 326 7 workshops workshop NOUN cana-572 326 8 on on ADP cana-572 326 9 recent recent ADJ cana-572 326 10 advances advance NOUN cana-572 326 11 and and CCONJ cana-572 326 12 innovations innovation NOUN cana-572 326 13 in in ADP cana-572 326 14 engineering engineering NOUN cana-572 326 15 ( ( PUNCT cana-572 326 16 icraie icraie PROPN cana-572 326 17 ) ) PUNCT cana-572 326 18 , , PUNCT cana-572 326 19 pp pp PROPN cana-572 326 20 . . PUNCT cana-572 327 1 1 1 NUM cana-572 327 2 - - SYM cana-572 327 3 5 5 NUM cana-572 327 4 . . PUNCT cana-572 327 5 ieee ieee NOUN cana-572 327 6 , , PUNCT cana-572 327 7 2018 2018 NUM cana-572 327 8 . . PUNCT cana-572 328 1 [ [ X cana-572 328 2 34 34 NUM cana-572 328 3 ] ] X cana-572 328 4 singh singh PROPN cana-572 328 5 , , PUNCT cana-572 328 6 pushpendra pushpendra PROPN cana-572 328 7 pratap pratap PROPN cana-572 328 8 , , PUNCT cana-572 328 9 m. m. NOUN cana-572 328 10 ram ram PROPN cana-572 328 11 kumar kumar PROPN cana-572 328 12 raja raja PROPN cana-572 328 13 , , PUNCT cana-572 328 14 ashish ashish PROPN cana-572 328 15 raj raj PROPN cana-572 328 16 , , PUNCT cana-572 328 17 and and CCONJ cana-572 328 18 mohammed mohammed PROPN cana-572 328 19 abdul abdul PROPN cana-572 328 20 muqeet muqeet PROPN cana-572 328 21 . . PUNCT cana-572 329 1 " " PUNCT cana-572 329 2 solution solution NOUN cana-572 329 3 to to ADP cana-572 329 4 interfacing interface VERB cana-572 329 5 problems problem NOUN cana-572 329 6 of of ADP cana-572 329 7 programmable programmable ADJ cana-572 329 8 logic logic NOUN cana-572 329 9 controller controller NOUN cana-572 329 10 in in ADP cana-572 329 11 hardware hardware NOUN cana-572 329 12 replacement replacement NOUN cana-572 329 13 . . PUNCT cana-572 329 14 " " PUNCT cana-572 330 1 in in ADP cana-572 330 2 2020 2020 NUM cana-572 330 3 5th 5th ADJ cana-572 330 4 ieee ieee NOUN cana-572 330 5 international international ADJ cana-572 330 6 conference conference NOUN cana-572 330 7 on on ADP cana-572 330 8 recent recent ADJ cana-572 330 9 advances advance NOUN cana-572 330 10 and and CCONJ cana-572 330 11 innovations innovation NOUN cana-572 330 12 in in ADP cana-572 330 13 engineering engineering NOUN cana-572 330 14 ( ( PUNCT cana-572 330 15 icraie icraie PROPN cana-572 330 16 ) ) PUNCT cana-572 330 17 , , PUNCT cana-572 330 18 pp pp PROPN cana-572 330 19 . . PUNCT cana-572 330 20 1 1 NUM cana-572 330 21 - - SYM cana-572 330 22 7 7 NUM cana-572 330 23 . . PUNCT cana-572 330 24 ieee ieee NOUN cana-572 330 25 , , PUNCT cana-572 330 26 2020 2020 NUM cana-572 330 27 . . PUNCT