{"id":"https://openalex.org/W7092298029","doi":"https://doi.org/10.1109/access.2025.3622660","title":"A Hybrid Framework for Acute Lymphoblastic Leukemia Identification Utilizing VIT-CNN Fusion and Immunologically Inspired Deep Feature Selection","display_name":"A Hybrid Framework for Acute Lymphoblastic Leukemia Identification Utilizing VIT-CNN Fusion and Immunologically Inspired Deep Feature Selection","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7092298029","doi":"https://doi.org/10.1109/access.2025.3622660"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3622660","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3622660","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.2025.3622660","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Abdulrahman Alabduljabbar","orcid":"https://orcid.org/0000-0002-1066-6725"},"institutions":[{"id":"https://openalex.org/I142608572","display_name":"Prince Sattam Bin Abdulaziz University","ror":"https://ror.org/04jt46d36","country_code":"SA","type":"education","lineage":["https://openalex.org/I142608572"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Abdulrahman Alabduljabbar","raw_affiliation_strings":["1Department of Information Systems, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0002-1066-6725","affiliations":[{"raw_affiliation_string":"1Department of Information Systems, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia","institution_ids":["https://openalex.org/I142608572"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Muhammad Awais","orcid":"https://orcid.org/0000-0003-3791-4140"},"institutions":[{"id":"https://openalex.org/I156216236","display_name":"Qassim University","ror":"https://ror.org/01wsfe280","country_code":"SA","type":"education","lineage":["https://openalex.org/I156216236"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Muhammad Awais","raw_affiliation_strings":["2Department of Computer Science, College of Computer, Qassim University, Buraydah, Qassim, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0003-3791-4140","affiliations":[{"raw_affiliation_string":"2Department of Computer Science, College of Computer, Qassim University, Buraydah, Qassim, Saudi Arabia","institution_ids":["https://openalex.org/I156216236"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tallha Akram","orcid":"https://orcid.org/0000-0003-4578-3849"},"institutions":[{"id":"https://openalex.org/I142608572","display_name":"Prince Sattam Bin Abdulaziz University","ror":"https://ror.org/04jt46d36","country_code":"SA","type":"education","lineage":["https://openalex.org/I142608572"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Tallha Akram","raw_affiliation_strings":["1Department of Information Systems, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0003-4578-3849","affiliations":[{"raw_affiliation_string":"1Department of Information Systems, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia","institution_ids":["https://openalex.org/I142608572"]}]},{"author_position":"last","author":{"id":null,"display_name":"Youssef N. Altherwy","orcid":null},"institutions":[{"id":"https://openalex.org/I142608572","display_name":"Prince Sattam Bin Abdulaziz University","ror":"https://ror.org/04jt46d36","country_code":"SA","type":"education","lineage":["https://openalex.org/I142608572"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Youssef N. Altherwy","raw_affiliation_strings":["1Department of Information Systems, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"1Department of Information Systems, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia","institution_ids":["https://openalex.org/I142608572"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I142608572"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.71026252,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"180355","last_page":"180374"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10978","display_name":"Prenatal Screening and Diagnostics","score":0.06210000067949295,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/T10978","display_name":"Prenatal Screening and Diagnostics","score":0.06210000067949295,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/T10290","display_name":"Pregnancy and preeclampsia studies","score":0.0364999994635582,"subfield":{"id":"https://openalex.org/subfields/2729","display_name":"Obstetrics and Gynecology"},"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/T13258","display_name":"Williams Syndrome Research","score":0.03319999948143959,"subfield":{"id":"https://openalex.org/subfields/2806","display_name":"Developmental Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5911999940872192},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5825999975204468},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5728999972343445},{"id":"https://openalex.org/keywords/lymphoblastic-leukemia","display_name":"Lymphoblastic Leukemia","score":0.4932999908924103},{"id":"https://openalex.org/keywords/blood-cancer","display_name":"Blood cancer","score":0.4587000012397766},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4336000084877014},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.40700000524520874},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.38830000162124634},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3783999979496002}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.734000027179718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7297000288963318},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5911999940872192},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5825999975204468},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5728999972343445},{"id":"https://openalex.org/C2909962599","wikidata":"https://www.wikidata.org/wiki/Q180664","display_name":"Lymphoblastic Leukemia","level":3,"score":0.4932999908924103},{"id":"https://openalex.org/C2992972558","wikidata":"https://www.wikidata.org/wiki/Q2509220","display_name":"Blood cancer","level":3,"score":0.4587000012397766},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4336000084877014},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4154999852180481},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.40700000524520874},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.38830000162124634},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3783999979496002},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.3752000033855438},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3659000098705292},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C2776954793","wikidata":"https://www.wikidata.org/wiki/Q1150780","display_name":"Clonal selection","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.2732999920845032},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.272599995136261},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.27140000462532043},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.2635999917984009},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.2590999901294708},{"id":"https://openalex.org/C2908731994","wikidata":"https://www.wikidata.org/wiki/Q2509220","display_name":"Hematologic Neoplasms","level":3,"score":0.2583000063896179},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.257099986076355}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3622660","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3622660","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:56c57f50b7404f8184bf67d3cf4ef515","is_oa":true,"landing_page_url":"https://doaj.org/article/56c57f50b7404f8184bf67d3cf4ef515","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 180355-180374 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3622660","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3622660","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":[{"score":0.4407217502593994,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G1358537763","display_name":null,"funder_award_id":"PSAU/2024/03/31876","funder_id":"https://openalex.org/F4320311227","funder_display_name":"Prince Sattam bin Abdulaziz University"}],"funders":[{"id":"https://openalex.org/F4320311227","display_name":"Prince Sattam bin Abdulaziz University","ror":"https://ror.org/04jt46d36"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Acute":[0],"Lymphoblastic":[1],"Leukemia":[2],"(ALL)":[3],"is":[4,30,151],"a":[5,77,105,186,193,213,231],"serious":[6],"blood":[7,17,23,85,182],"cancer":[8],"characterized":[9],"by":[10,69,135],"the":[11,89,136,166,172,216,243],"abnormal":[12],"growth":[13],"of":[14,91,118,147,171,189,206,234,252],"progenitor":[15],"white":[16],"cells,":[18],"which":[19],"interferes":[20],"with":[21,159,212,236],"normal":[22],"cell":[24],"production.":[25],"Early":[26],"and":[27,35,71,94,104,115,126,141,169,222,239],"precise":[28],"detection":[29],"essential":[31],"for":[32,80,208],"effective":[33],"treatment":[34],"better":[36],"patient":[37],"outcomes.":[38],"Convolutional":[39],"neural":[40],"networks":[41],"(CNNs)":[42],"have":[43],"shown":[44],"significant":[45],"promise":[46],"in":[47,65,215,250],"automating":[48],"diagnostic":[49],"processes":[50],"within":[51],"digital":[52],"pathology.":[53],"However,":[54],"classifying":[55],"ALL":[56,82,190,210],"subtypes":[57],"remains":[58],"challenging":[59],"due":[60],"to":[61,111,154],"subtle":[62],"morphological":[63],"differences":[64],"lymphoblast":[66],"features":[67,123,150],"compounded":[68],"small":[70],"imbalanced":[72],"datasets.":[73],"This":[74],"paper":[75],"presents":[76],"hybrid":[78],"framework":[79],"improved":[81],"classification":[83],"from":[84,185],"smear":[86,183],"images,":[87],"leveraging":[88],"strengths":[90],"deep":[92],"learning":[93],"immunological":[95,130],"optimization.":[96],"The":[97,121,144,199],"proposed":[98,173,200,244],"approach":[99,245],"integrates":[100],"Vision":[101],"Transformer":[102],"(ViT-B/16)":[103],"customized":[106],"CNN":[107],"as":[108],"feature":[109,217],"extractors":[110],"capture":[112],"both":[113],"global":[114],"local":[116],"representations":[117],"leukemia-related":[119],"patterns.":[120],"extracted":[122],"are":[124],"fused":[125],"optimized":[127],"using":[128],"an":[129,203],"clonal":[131],"selection":[132,142],"algorithm,":[133],"inspired":[134],"adaptive":[137],"immune":[138],"system\u2019s":[139],"mutation":[140],"process.":[143],"reduced":[145],"set":[146],"best":[148],"selected":[149],"subsequently":[152],"utilized":[153],"train":[155],"various":[156,197],"baseline":[157],"classifiers":[158],"diverse":[160],"kernel":[161],"configurations.":[162],"To":[163],"rigorously":[164],"validate":[165],"generalization":[167],"ability":[168],"robustness":[170],"approach,":[174],"this":[175],"study":[176],"leverages":[177],"well-established":[178],"datasets":[179],"that":[180],"include":[181],"images":[184],"broad":[187],"spectrum":[188],"classes,":[191],"ensuring":[192],"comprehensive":[194],"assessment":[195],"across":[196],"conditions.":[198],"method":[201],"achieves":[202],"average":[204],"accuracy":[205,233],"98%":[207,223],"binary":[209],"classification,":[211,228],"60%reduction":[214],"vector,":[218],"alongside":[219],"97.9%":[220],"precision":[221,238],"sensitivity.":[224,241],"For":[225],"B-ALL":[226],"subtype":[227],"it":[229],"reaches":[230],"maximum":[232],"98.7%,":[235],"98.8%":[237],"97%":[240],"Overall,":[242],"surpasses":[246],"several":[247],"existing":[248],"methods":[249],"terms":[251],"key":[253],"performance":[254],"metrics.":[255]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-18T00:00:00"}
