{"id":"https://openalex.org/W4381430845","doi":"https://doi.org/10.3233/jifs-231776","title":"Computer-aided diagnosis using white shark optimizer with attention-based deep learning for breast cancer classification","display_name":"Computer-aided diagnosis using white shark optimizer with attention-based deep learning for breast cancer classification","publication_year":2023,"publication_date":"2023-05-30","ids":{"openalex":"https://openalex.org/W4381430845","doi":"https://doi.org/10.3233/jifs-231776"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-231776","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-231776","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051377398","display_name":"R. K. Chandana Mani","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R.K. Chandana Mani","raw_affiliation_strings":["School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India"],"affiliations":[{"raw_affiliation_string":"School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056852260","display_name":"J Kamalakannan","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"J. Kamalakannan","raw_affiliation_strings":["School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India"],"affiliations":[{"raw_affiliation_string":"School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India","institution_ids":["https://openalex.org/I876193797"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5056852260"],"corresponding_institution_ids":["https://openalex.org/I876193797"],"apc_list":null,"apc_paid":null,"fwci":1.044,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80956522,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"45","issue":"2","first_page":"2641","last_page":"2655"},"is_retracted":true,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9890000224113464,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9799000024795532,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7560306787490845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7503728866577148},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6183760762214661},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.6048528552055359},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5724368691444397},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5308139324188232},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5281115770339966},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.522558867931366},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5055878162384033},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.49397140741348267},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.27757471799850464},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.09865203499794006}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7560306787490845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7503728866577148},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6183760762214661},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.6048528552055359},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5724368691444397},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5308139324188232},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5281115770339966},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.522558867931366},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5055878162384033},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.49397140741348267},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.27757471799850464},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09865203499794006},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-231776","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-231776","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.8399999737739563,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W2344480160","https://openalex.org/W2609584387","https://openalex.org/W2708846726","https://openalex.org/W2716665989","https://openalex.org/W2791915981","https://openalex.org/W2806435421","https://openalex.org/W2892961888","https://openalex.org/W2972535786","https://openalex.org/W2998864442","https://openalex.org/W3003199121","https://openalex.org/W3006425969","https://openalex.org/W3044145473","https://openalex.org/W3114879287","https://openalex.org/W3126637267","https://openalex.org/W3134709347","https://openalex.org/W3135765136","https://openalex.org/W3168884242","https://openalex.org/W3185157984","https://openalex.org/W3191219235","https://openalex.org/W3197877042","https://openalex.org/W3205707234","https://openalex.org/W3211713681","https://openalex.org/W3217602012","https://openalex.org/W4200507480","https://openalex.org/W4200566810","https://openalex.org/W4205943221","https://openalex.org/W4206773083","https://openalex.org/W4210260155","https://openalex.org/W4211169133","https://openalex.org/W4213182863","https://openalex.org/W4214629996","https://openalex.org/W4214838039","https://openalex.org/W4221053294","https://openalex.org/W4229062925","https://openalex.org/W4229459202","https://openalex.org/W4280590704","https://openalex.org/W4283215393","https://openalex.org/W4284683049","https://openalex.org/W4284971318","https://openalex.org/W4285388909","https://openalex.org/W4296083357","https://openalex.org/W4298126680","https://openalex.org/W4306180875","https://openalex.org/W4307021520","https://openalex.org/W4312175638","https://openalex.org/W4313362506","https://openalex.org/W4318819419","https://openalex.org/W4365815661","https://openalex.org/W4367047386","https://openalex.org/W6736524840","https://openalex.org/W6740537426","https://openalex.org/W6740617645","https://openalex.org/W6791903657","https://openalex.org/W6807769407"],"related_works":["https://openalex.org/W2140186469","https://openalex.org/W4390421286","https://openalex.org/W4280563792","https://openalex.org/W4389724018","https://openalex.org/W4318719684","https://openalex.org/W4318559728","https://openalex.org/W3183136280","https://openalex.org/W2775233965","https://openalex.org/W3114716045","https://openalex.org/W4360995913"],"abstract_inverted_index":{"Breast":[0],"cancer":[1,9,123,136],"(BC)":[2],"is":[3,35,151],"categorized":[4],"as":[5],"the":[6,13,23,27,45,85,91,97,121,134,141,144,155,159,168,174,193,197,214],"most":[7],"widespread":[8],"among":[10],"women":[11],"throughout":[12],"world.":[14],"The":[15,76,127,201,209],"earlier":[16],"analysis":[17],"of":[18,26,48,88,94,99,176,192,207],"BC":[19,29,57,80],"assists":[20],"to":[21,55,153,221],"increase":[22],"survival":[24],"rate":[25],"disease.":[28],"diagnosis":[30,81,110],"on":[31,58,82],"histopathology":[32],"images":[33,89,178],"(HIS)":[34],"a":[36,108,112],"tedious":[37],"process":[38],"that":[39,213],"includes":[40],"recognizing":[41],"cancerous":[42],"regions":[43],"within":[44],"microscopic":[46],"image":[47,67,156],"breast":[49,122,135],"tissue.":[50],"There":[51],"are":[52,84],"various":[53],"methods":[54],"discovering":[56],"HSI,":[59],"namely":[60],"deep":[61,118],"learning":[62,72,119],"(DL)":[63],"based":[64,74,148],"methods,":[65],"classical":[66],"processing":[68],"techniques,":[69],"and":[70,90],"machine":[71],"(ML)":[73],"methods.":[75],"major":[77],"problems":[78],"in":[79,96],"HSI":[83],"larger":[86],"size":[87],"high":[92],"degree":[93],"variability":[95],"appearance":[98],"tumorous":[100],"regions.":[101],"With":[102],"this":[103,105],"motivation,":[104],"study":[106],"develops":[107],"computer-aided":[109],"using":[111,137,181],"white":[113],"shark":[114],"optimizer":[115],"with":[116,163],"attention-based":[117,182],"for":[120],"classification":[124,133,175],"(WSO-ABDLBCC)":[125],"model.":[126],"presented":[128],"WSO-ABDLBCC":[129,142,194,215],"technique":[130,216],"performs":[131,167],"accurate":[132],"DL":[138],"techniques.":[139],"In":[140],"technique,":[143],"Guided":[145],"filtering":[146],"(GF)":[147],"noise":[149],"removal":[150],"applied":[152],"improve":[154],"quality.":[157],"Next,":[158],"Faster":[160],"SqueezeNet":[161],"model":[162,203],"WSO-based":[164],"hyperparameter":[165],"tuning":[166],"feature":[169],"vector":[170],"generation":[171],"process.":[172],"Finally,":[173],"histopathological":[177],"takes":[179],"place":[180],"bidirectional":[183],"long":[184],"short-term":[185],"memory":[186],"(ABiLSTM).":[187],"A":[188],"detailed":[189],"experimental":[190,210],"validation":[191],"occurs":[195],"utilizing":[196],"benchmark":[198],"Breakhis":[199],"database.":[200],"proposed":[202],"achieved":[204],"an":[205],"accuracy":[206],"95.2%.":[208],"outcomes":[211],"portrayed":[212],"accomplishes":[217],"improved":[218],"performance":[219],"compared":[220],"other":[222],"existing":[223],"models.":[224]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}