{"id":"https://openalex.org/W4414630944","doi":"https://doi.org/10.1109/access.2025.3616022","title":"Attention-Based Convolutional Neural Network Model for Skin Cancer Classification","display_name":"Attention-Based Convolutional Neural Network Model for Skin Cancer Classification","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414630944","doi":"https://doi.org/10.1109/access.2025.3616022"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3616022","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3616022","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3616022","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101654685","display_name":"Mohamed Hosny","orcid":"https://orcid.org/0009-0007-4039-4525"},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mohamed Hosny","raw_affiliation_strings":["IRC for Finance and Digital Economy, KFUPM Business School, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia"],"raw_orcid":"https://orcid.org/0009-0007-4039-4525","affiliations":[{"raw_affiliation_string":"IRC for Finance and Digital Economy, KFUPM Business School, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030075164","display_name":"Ibrahim A. Elgendy","orcid":"https://orcid.org/0000-0001-7154-2307"},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Ibrahim A. Elgendy","raw_affiliation_strings":["IRC for Finance and Digital Economy, KFUPM Business School, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0001-7154-2307","affiliations":[{"raw_affiliation_string":"IRC for Finance and Digital Economy, KFUPM Business School, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064393648","display_name":"Samia Allaoua Chelloug","orcid":"https://orcid.org/0000-0002-9711-0235"},"institutions":[{"id":"https://openalex.org/I106778892","display_name":"Princess Nourah bint Abdulrahman University","ror":"https://ror.org/05b0cyh02","country_code":"SA","type":"education","lineage":["https://openalex.org/I106778892"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Samia Allaoua Chelloug","raw_affiliation_strings":["Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-9711-0235","affiliations":[{"raw_affiliation_string":"Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I106778892"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044406722","display_name":"Mousa Albashrawi","orcid":"https://orcid.org/0000-0002-6269-1658"},"institutions":[{"id":"https://openalex.org/I134085113","display_name":"King Fahd University of Petroleum and Minerals","ror":"https://ror.org/03yez3163","country_code":"SA","type":"education","lineage":["https://openalex.org/I134085113"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mousa Ahmad Albashrawi","raw_affiliation_strings":["IRC for Finance and Digital Economy, KFUPM Business School, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-6269-1658","affiliations":[{"raw_affiliation_string":"IRC for Finance and Digital Economy, KFUPM Business School, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia","institution_ids":["https://openalex.org/I134085113"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.5418,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.91004604,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"172027","last_page":"172050"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7317000031471252},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5178999900817871},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5126000046730042},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5044999718666077},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.45669999718666077},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.43050000071525574},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4090999960899353},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3935000002384186},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.39239999651908875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.814300000667572},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7778000235557556},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7317000031471252},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5178999900817871},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5126000046730042},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5092999935150146},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5044999718666077},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.45669999718666077},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.43050000071525574},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4090999960899353},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3935000002384186},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.39239999651908875},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.38429999351501465},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3804999887943268},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3447999954223633},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.3422999978065491},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.3393999934196472},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3337000012397766},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C2777789703","wikidata":"https://www.wikidata.org/wiki/Q192102","display_name":"Skin cancer","level":3,"score":0.30300000309944153},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.29339998960494995},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.28859999775886536},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.26429998874664307}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3616022","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3616022","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4a835cd07b2341a184055ccc01220042","is_oa":true,"landing_page_url":"https://doaj.org/article/4a835cd07b2341a184055ccc01220042","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 172027-172050 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3616022","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3616022","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8244502498","display_name":null,"funder_award_id":"PNURSP2025R239","funder_id":"https://openalex.org/F4320322484","funder_display_name":"Princess Nourah Bint Abdulrahman University"}],"funders":[{"id":"https://openalex.org/F4320322484","display_name":"Princess Nourah Bint Abdulrahman University","ror":"https://ror.org/05b0cyh02"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1984132569","https://openalex.org/W2794825826","https://openalex.org/W2956922850","https://openalex.org/W3127990383","https://openalex.org/W3158436118","https://openalex.org/W3183919471","https://openalex.org/W3199013370","https://openalex.org/W4205189720","https://openalex.org/W4210791664","https://openalex.org/W4214575762","https://openalex.org/W4220785415","https://openalex.org/W4224037877","https://openalex.org/W4284680265","https://openalex.org/W4294934958","https://openalex.org/W4311304837","https://openalex.org/W4316673314","https://openalex.org/W4318820267","https://openalex.org/W4322494898","https://openalex.org/W4362605342","https://openalex.org/W4362620048","https://openalex.org/W4365518054","https://openalex.org/W4366150712","https://openalex.org/W4385989325","https://openalex.org/W4387435339","https://openalex.org/W4387546350","https://openalex.org/W4390665799","https://openalex.org/W4391969958","https://openalex.org/W4392173253","https://openalex.org/W4392338550","https://openalex.org/W4392614533","https://openalex.org/W4392945653","https://openalex.org/W4393405726","https://openalex.org/W4395477921","https://openalex.org/W4399040877","https://openalex.org/W4399659744","https://openalex.org/W4399727051","https://openalex.org/W4400003647","https://openalex.org/W4400768228","https://openalex.org/W4401047670","https://openalex.org/W4402215456","https://openalex.org/W4404276110","https://openalex.org/W4404331078","https://openalex.org/W4406026061","https://openalex.org/W4406898111","https://openalex.org/W4407253071","https://openalex.org/W4407294474","https://openalex.org/W4407338216","https://openalex.org/W4409784552","https://openalex.org/W4409839145","https://openalex.org/W4410842332","https://openalex.org/W4411152384"],"related_works":[],"abstract_inverted_index":{"Early":[0],"detection":[1],"of":[2,20,51,55,81,183,236],"skin":[3],"cancer":[4],"(SC)":[5],"is":[6,140,162],"paramount":[7],"for":[8,187,204,221],"effective":[9],"treatment.":[10],"Although":[11],"convolutional":[12],"neural":[13],"networks":[14],"(CNN)":[15],"have":[16],"facilitated":[17],"automated":[18,205],"learning":[19,40,238],"high-level":[21],"features":[22,128],"from":[23],"dermoscopic":[24,174],"images,":[25],"many":[26],"prior":[27],"studies":[28],"relied":[29],"on":[30],"separate":[31],"feature":[32,122],"extraction":[33],"and":[34,47,150,178,239],"selection":[35],"stages":[36],"combined":[37],"with":[38,148,181,212,244],"machine":[39],"classifiers,":[41],"resulting":[42],"in":[43,97,115,233],"increased":[44],"model":[45,109,168],"complexity":[46],"a":[48,120,134,143,201,230],"higher":[49],"risk":[50],"overfitting.":[52],"Furthermore,":[53],"sensitivity":[54],"conventional":[56],"CNNs":[57],"to":[58,68,125,154,164,223],"subtle":[59],"lesion":[60,116],"changes":[61],"can":[62],"be":[63],"challenging":[64],"without":[65],"inherent":[66],"mechanisms":[67],"emphasize":[69],"salient":[70],"image":[71,225],"regions,":[72],"ultimately":[73],"hindering":[74],"classification":[75,226],"performance.":[76],"Moreover,":[77,216],"the":[78,89,166,234],"ambiguous":[79],"nature":[80],"these":[82],"models":[83],"often":[84],"leaves":[85],"dermatologists":[86],"uncertain":[87],"about":[88],"reasoning":[90],"behind":[91],"predictions,":[92],"which":[93],"limits":[94],"their":[95],"adoption":[96],"clinical":[98],"settings.":[99],"Therefore,":[100],"we":[101],"propose":[102],"an":[103],"efficient":[104,136,245],"dual":[105,137],"attention-based":[106],"ResNet50":[107],"(EDA-ResNet50)":[108],"that":[110],"effectively":[111,126],"captures":[112],"vital":[113],"details":[114],"areas.":[117],"EDA-ResNet50":[118,167,189,197,217,228],"integrates":[119],"multi-scale":[121],"representation":[123],"block":[124],"capture":[127],"across":[129],"various":[130],"spatial":[131,151],"scales.":[132],"Additionally,":[133],"unique":[135],"attention":[138,152],"module":[139],"introduced,":[141],"amalgamating":[142],"lightweight":[144],"convolution-based":[145],"recalibration":[146],"unit":[147],"channel":[149],"blocks":[153],"enhance":[155],"information":[156],"flow.":[157],"Gradient-weighted":[158],"class":[159],"activation":[160],"mapping":[161],"exploited":[163],"understand":[165],"decisions.":[169],"The":[170],"proposed":[171],"system":[172],"classifies":[173],"images":[175],"into":[176],"benign":[177],"malignant":[179],"categories":[180],"accuracy":[182,211],"93.18%,":[184],"offering":[185],"confidence":[186],"dermatologist.":[188],"outperformed":[190],"several":[191],"CNN":[192],"techniques.":[193],"Unlike":[194],"existing":[195],"studies,":[196],"streamlined":[198],"architecture":[199],"presents":[200,229],"compelling":[202],"solution":[203],"SC":[206],"classification,":[207],"combining":[208],"high":[209],"diagnostic":[210,246],"low":[213],"computational":[214],"overhead.":[215],"holds":[218],"significant":[219],"potential":[220],"application":[222],"other":[224],"tasks.":[227],"new":[231],"frontier":[232],"intersection":[235],"deep":[237],"healthcare,":[240],"empowering":[241],"medical":[242],"professionals":[243],"tools.":[247]},"counts_by_year":[{"year":2026,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}