{"id":"https://openalex.org/W4411012801","doi":"https://doi.org/10.1007/s12530-025-09698-6","title":"Healthcare fraud detection using adaptive learning and deep learning techniques","display_name":"Healthcare fraud detection using adaptive learning and deep learning techniques","publication_year":2025,"publication_date":"2025-06-01","ids":{"openalex":"https://openalex.org/W4411012801","doi":"https://doi.org/10.1007/s12530-025-09698-6"},"language":"en","primary_location":{"id":"doi:10.1007/s12530-025-09698-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12530-025-09698-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12530-025-09698-6.pdf","source":{"id":"https://openalex.org/S202254422","display_name":"Evolving Systems","issn_l":"1868-6478","issn":["1868-6478","1868-6486"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Evolving Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s12530-025-09698-6.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016362237","display_name":"Irum Matloob","orcid":"https://orcid.org/0000-0002-5425-2321"},"institutions":[{"id":"https://openalex.org/I6292670","display_name":"Fatima Jinnah Women University","ror":"https://ror.org/009026n40","country_code":"PK","type":"education","lineage":["https://openalex.org/I6292670"]}],"countries":["PK"],"is_corresponding":true,"raw_author_name":"Irum Matloob","raw_affiliation_strings":["Fatima Jinnah Women University, Rawalpindi, Pakistan"],"affiliations":[{"raw_affiliation_string":"Fatima Jinnah Women University, Rawalpindi, Pakistan","institution_ids":["https://openalex.org/I6292670"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050441398","display_name":"Shoab Ahmed Khan","orcid":"https://orcid.org/0000-0003-0265-8204"},"institutions":[{"id":"https://openalex.org/I6292670","display_name":"Fatima Jinnah Women University","ror":"https://ror.org/009026n40","country_code":"PK","type":"education","lineage":["https://openalex.org/I6292670"]},{"id":"https://openalex.org/I929597975","display_name":"National University of Sciences and Technology","ror":"https://ror.org/03w2j5y17","country_code":"PK","type":"education","lineage":["https://openalex.org/I929597975"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Shoab Khan","raw_affiliation_strings":["Fatima Jinnah Women University, Rawalpindi, Pakistan","National university of science and technology (NUST), Islamabad, Pakistan"],"affiliations":[{"raw_affiliation_string":"Fatima Jinnah Women University, Rawalpindi, Pakistan","institution_ids":["https://openalex.org/I6292670"]},{"raw_affiliation_string":"National university of science and technology (NUST), Islamabad, Pakistan","institution_ids":["https://openalex.org/I929597975"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041764145","display_name":"Rukaiya Rukaiya","orcid":null},"institutions":[{"id":"https://openalex.org/I34478861","display_name":"Sir Syed University of Engineering and Technology","ror":"https://ror.org/02n4kqn31","country_code":"PK","type":"education","lineage":["https://openalex.org/I34478861"]},{"id":"https://openalex.org/I6292670","display_name":"Fatima Jinnah Women University","ror":"https://ror.org/009026n40","country_code":"PK","type":"education","lineage":["https://openalex.org/I6292670"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Rukaiya Rukaiya","raw_affiliation_strings":["Fatima Jinnah Women University, Rawalpindi, Pakistan","Sir Syed University of Engineering and Technology, Karachi, Pakistan"],"affiliations":[{"raw_affiliation_string":"Fatima Jinnah Women University, Rawalpindi, Pakistan","institution_ids":["https://openalex.org/I6292670"]},{"raw_affiliation_string":"Sir Syed University of Engineering and Technology, Karachi, Pakistan","institution_ids":["https://openalex.org/I34478861"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117823574","display_name":"Hessa Alfraihi","orcid":"https://orcid.org/0000-0001-8169-3766"},"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":"Hessa Alfraihi","raw_affiliation_strings":["Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia","institution_ids":["https://openalex.org/I106778892"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070343465","display_name":"Javed Ali Khan","orcid":"https://orcid.org/0000-0003-3306-1195"},"institutions":[{"id":"https://openalex.org/I141584323","display_name":"University of Hertfordshire","ror":"https://ror.org/0267vjk41","country_code":"GB","type":"education","lineage":["https://openalex.org/I141584323"]},{"id":"https://openalex.org/I6292670","display_name":"Fatima Jinnah Women University","ror":"https://ror.org/009026n40","country_code":"PK","type":"education","lineage":["https://openalex.org/I6292670"]}],"countries":["GB","PK"],"is_corresponding":false,"raw_author_name":"Javed Ali Khan","raw_affiliation_strings":["Department of Computer Science, University of Hertfordshire,  Hertfordshire, UK","Fatima Jinnah Women University, Rawalpindi, Pakistan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Hertfordshire,  Hertfordshire, UK","institution_ids":["https://openalex.org/I141584323"]},{"raw_affiliation_string":"Fatima Jinnah Women University, Rawalpindi, Pakistan","institution_ids":["https://openalex.org/I6292670"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5016362237"],"corresponding_institution_ids":["https://openalex.org/I6292670"],"apc_list":{"value":2590,"currency":"EUR","value_usd":3190},"apc_paid":{"value":2590,"currency":"EUR","value_usd":3190},"fwci":11.7157,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.98154446,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"16","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9958999752998352,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9958999752998352,"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/T14400","display_name":"Medical Coding and Health Information","score":0.9441999793052673,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T13643","display_name":"Artificial Intelligence in Law","score":0.9435999989509583,"subfield":{"id":"https://openalex.org/subfields/3320","display_name":"Political Science and International Relations"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7137623429298401},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.52027827501297},{"id":"https://openalex.org/keywords/complex-system","display_name":"Complex system","score":0.5174927711486816},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5134199857711792},{"id":"https://openalex.org/keywords/healthcare-system","display_name":"Healthcare system","score":0.5079503655433655},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.4621826410293579},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4584377408027649},{"id":"https://openalex.org/keywords/adaptive-learning","display_name":"Adaptive learning","score":0.4476828873157501},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3955356478691101}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7137623429298401},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.52027827501297},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.5174927711486816},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5134199857711792},{"id":"https://openalex.org/C2988170871","wikidata":"https://www.wikidata.org/wiki/Q11000047","display_name":"Healthcare system","level":3,"score":0.5079503655433655},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.4621826410293579},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4584377408027649},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.4476828873157501},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3955356478691101},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s12530-025-09698-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12530-025-09698-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12530-025-09698-6.pdf","source":{"id":"https://openalex.org/S202254422","display_name":"Evolving Systems","issn_l":"1868-6478","issn":["1868-6478","1868-6486"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Evolving Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s12530-025-09698-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12530-025-09698-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12530-025-09698-6.pdf","source":{"id":"https://openalex.org/S202254422","display_name":"Evolving Systems","issn_l":"1868-6478","issn":["1868-6478","1868-6486"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Evolving Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4000000059604645}],"awards":[{"id":"https://openalex.org/G2053653470","display_name":null,"funder_award_id":"PNURSP","funder_id":"https://openalex.org/F4320322484","funder_display_name":"Princess Nourah Bint Abdulrahman University"},{"id":"https://openalex.org/G4010074732","display_name":null,"funder_award_id":"Riyadh","funder_id":"https://openalex.org/F4320322484","funder_display_name":"Princess Nourah Bint Abdulrahman University"},{"id":"https://openalex.org/G5094159666","display_name":null,"funder_award_id":"PNURSP2025R411","funder_id":"https://openalex.org/F4320322484","funder_display_name":"Princess Nourah Bint Abdulrahman University"},{"id":"https://openalex.org/G6063645514","display_name":null,"funder_award_id":"PNURSP2025R","funder_id":"https://openalex.org/F4320322484","funder_display_name":"Princess Nourah Bint Abdulrahman University"},{"id":"https://openalex.org/G7895878613","display_name":null,"funder_award_id":"PNURSP2025R4","funder_id":"https://openalex.org/F4320322484","funder_display_name":"Princess Nourah Bint Abdulrahman University"},{"id":"https://openalex.org/G8978955634","display_name":null,"funder_award_id":"PNURSP2025R41","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":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411012801.pdf","grobid_xml":"https://content.openalex.org/works/W4411012801.grobid-xml"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W1003236940","https://openalex.org/W1496887273","https://openalex.org/W1555474281","https://openalex.org/W1788246168","https://openalex.org/W1968573882","https://openalex.org/W1990557724","https://openalex.org/W2040714331","https://openalex.org/W2071855775","https://openalex.org/W2078187416","https://openalex.org/W2083408233","https://openalex.org/W2093915710","https://openalex.org/W2094510831","https://openalex.org/W2132035238","https://openalex.org/W2133841540","https://openalex.org/W2136266424","https://openalex.org/W2345503783","https://openalex.org/W2500491302","https://openalex.org/W2556066909","https://openalex.org/W2564754306","https://openalex.org/W2577748110","https://openalex.org/W2584158425","https://openalex.org/W2586094575","https://openalex.org/W2587209343","https://openalex.org/W2736186583","https://openalex.org/W2755041628","https://openalex.org/W2760506815","https://openalex.org/W2765732590","https://openalex.org/W2768495044","https://openalex.org/W2782767340","https://openalex.org/W2787707077","https://openalex.org/W2891484158","https://openalex.org/W2892493782","https://openalex.org/W2919823329","https://openalex.org/W2971477033","https://openalex.org/W2998188726","https://openalex.org/W3000561819","https://openalex.org/W3045899807","https://openalex.org/W3047216992","https://openalex.org/W3126999983","https://openalex.org/W4200514525","https://openalex.org/W4210915621","https://openalex.org/W4252280657","https://openalex.org/W4283019702","https://openalex.org/W4283260398","https://openalex.org/W4283645865","https://openalex.org/W4300907080","https://openalex.org/W4312226679","https://openalex.org/W4387308661","https://openalex.org/W4391374550","https://openalex.org/W4392941152","https://openalex.org/W4393204115","https://openalex.org/W4401387685","https://openalex.org/W4402158565","https://openalex.org/W4402260864","https://openalex.org/W4402277702","https://openalex.org/W4407402407","https://openalex.org/W6603584607"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W2804383999","https://openalex.org/W4380075502"],"abstract_inverted_index":{"The":[0,290,298],"healthcare":[1,21,40,56,59,79,135],"industry":[2,117],"faces":[3],"huge":[4],"losses":[5],"due":[6],"to":[7,14,76,106,140,156,185,266,282],"the":[8,15,49,107,116,129,134,169,174,187,201,207,215,224,235,256,261,268,272,276,280,293,304,312,317],"mismanagement":[9],"of":[10,17,51,109,133,144,189,229,255,292,307],"insurance":[11,103,305],"transactions.":[12],"Due":[13,105],"development":[16],"public":[18],"and":[19,54,63,90,123,171,179,220,249,260,311],"private":[20],"programs,":[22],"many":[23],"citizens":[24],"receive":[25],"better":[26],"medical":[27,110],"care":[28],"benefits.":[29],"Still,":[30],"there":[31],"is":[32,68,296],"a":[33,45,78,97,162,246],"need":[34],"for":[35,100],"financial":[36],"transparency":[37],"in":[38,66,115],"these":[39,230],"transactions,":[41],"which":[42],"has":[43,315],"become":[44],"challenge.":[46],"To":[47],"ensure":[48],"delivery":[50],"more":[52],"effective":[53],"higher-quality":[55],"services,":[57,122],"introducing":[58],"fraudulent":[60,113,146,250],"transactions":[61,114,147],"prevention":[62],"detection":[64,153],"tools":[65],"hospitals":[67],"necessary.":[69],"In":[70],"this":[71,94],"paper,":[72],"we":[73,160],"propose":[74],"how":[75],"inculcate":[77],"transaction":[80],"monitoring":[81],"system":[82],"within":[83],"an":[84,150,182],"enterprise":[85],"or":[86],"organisation.":[87],"Using":[88],"machine":[89],"deep":[91],"learning":[92],"techniques,":[93],"research":[95],"proposes":[96],"novel":[98],"framework":[99,154,163,295],"analyzing":[101],"health":[102],"data.":[104],"complexity":[108],"information,":[111],"detecting":[112],"requires":[118],"effort.":[119],"Typically,":[120],"patients,":[121],"providers":[124],"(doctors,":[125],"hospitals,":[126],"pharmacies)":[127],"are":[128,196,199,205,213,222,232,243,252,264,274,301],"main":[130],"key":[131],"elements":[132,231],"ecosystem.":[136],"As":[137],"fraudsters":[138],"continue":[139],"evolve":[141],"their":[142],"methods":[143],"conducting":[145],"over":[148],"time,":[149],"evolving":[151],"fraud":[152,167,319],"needs":[155],"be":[157],"developed.":[158],"Therefore,":[159],"proposed":[161,277,294],"that":[164,190],"can":[165],"identify":[166,267],"at":[168,200,206,214,223],"actor-level":[170],"further":[172],"analyze":[173],"identified":[175,192],"element":[176],"(doctor,":[177],"patient,":[178],"services)":[180],"using":[181,245,303],"Anomaly":[183,236,262],"transformer":[184],"evaluate":[186],"behavior":[188],"particular":[191],"element.":[193,289],"Actor-level":[194],"frauds":[195,273],"detected,":[197],"50%":[198],"patient":[202,218,239],"level,":[203,211,219],"12%":[204],"service":[208,216],"versus":[209,217],"doctor":[210],"13%":[212],"25%":[221],"physician":[225],"level.":[226],"Further,":[227],"sequences":[228,251],"analyzed":[233],"by":[234],"transformer.":[237],"All":[238],"sequences\u2019":[240],"anomaly":[241,269],"scores":[242],"generated":[244],"data-driven":[247],"threshold,":[248],"identified.":[253],"Results":[254],"Speciality-based":[257],"Rule":[258],"engine":[259],"transformers":[263],"compared":[265],"finally.":[270],"Once":[271],"identified,":[275],"architecture":[278],"enables":[279],"management":[281],"take":[283],"disciplinary":[284],"action":[285],"against":[286],"each":[287],"involved":[288],"Accuracy":[291],"97%,":[297],"experimental":[299],"results":[300],"validated":[302,316],"data":[306],"local":[308],"hospital":[309],"employees,":[310],"domain":[313],"expert":[314],"detected":[318],"cases.":[320]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}