{"id":"https://openalex.org/W4412021324","doi":"https://doi.org/10.1109/cbms65348.2025.00181","title":"Fraud, Waste, and Abuse Detection in Medical Claims Using an Ensemble of Unsupervised Machine Learning Models","display_name":"Fraud, Waste, and Abuse Detection in Medical Claims Using an Ensemble of Unsupervised Machine Learning Models","publication_year":2025,"publication_date":"2025-06-18","ids":{"openalex":"https://openalex.org/W4412021324","doi":"https://doi.org/10.1109/cbms65348.2025.00181"},"language":"en","primary_location":{"id":"doi:10.1109/cbms65348.2025.00181","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbms65348.2025.00181","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 38th International Symposium on Computer-Based Medical Systems (CBMS)","raw_type":"proceedings-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/A5118817776","display_name":"Willem A. Janse Van Rensburg","orcid":null},"institutions":[{"id":"https://openalex.org/I26092322","display_name":"Stellenbosch University","ror":"https://ror.org/05bk57929","country_code":"ZA","type":"education","lineage":["https://openalex.org/I26092322"]}],"countries":["ZA"],"is_corresponding":true,"raw_author_name":"Willem A. Janse Van Rensburg","raw_affiliation_strings":["Stellenbosch University,Department of Electrical & Electronic Engineering,Stellenbosch,South Africa"],"affiliations":[{"raw_affiliation_string":"Stellenbosch University,Department of Electrical & Electronic Engineering,Stellenbosch,South Africa","institution_ids":["https://openalex.org/I26092322"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070191995","display_name":"Chantelle Y. Van Staden","orcid":"https://orcid.org/0000-0001-8000-3583"},"institutions":[{"id":"https://openalex.org/I26092322","display_name":"Stellenbosch University","ror":"https://ror.org/05bk57929","country_code":"ZA","type":"education","lineage":["https://openalex.org/I26092322"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Chantelle Van Staden","raw_affiliation_strings":["Stellenbosch University,Department of Electrical & Electronic Engineering,Stellenbosch,South Africa"],"affiliations":[{"raw_affiliation_string":"Stellenbosch University,Department of Electrical & Electronic Engineering,Stellenbosch,South Africa","institution_ids":["https://openalex.org/I26092322"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078511208","display_name":"Lise Prinsloo","orcid":null},"institutions":[{"id":"https://openalex.org/I26092322","display_name":"Stellenbosch University","ror":"https://ror.org/05bk57929","country_code":"ZA","type":"education","lineage":["https://openalex.org/I26092322"]}],"countries":["ZA"],"is_corresponding":false,"raw_author_name":"Lise Prinsloo","raw_affiliation_strings":["Stellenbosch University,Department of Electrical & Electronic Engineering,Stellenbosch,South Africa"],"affiliations":[{"raw_affiliation_string":"Stellenbosch University,Department of Electrical & Electronic Engineering,Stellenbosch,South Africa","institution_ids":["https://openalex.org/I26092322"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5118817776"],"corresponding_institution_ids":["https://openalex.org/I26092322"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.31865828,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12339","display_name":"Medical Malpractice and Liability Issues","score":0.6930999755859375,"subfield":{"id":"https://openalex.org/subfields/3611","display_name":"Pharmacy"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T12339","display_name":"Medical Malpractice and Liability Issues","score":0.6930999755859375,"subfield":{"id":"https://openalex.org/subfields/3611","display_name":"Pharmacy"},"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/T13945","display_name":"Legal, Health, Environmental and COVID-19 Challenges","score":0.6154999732971191,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational 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/T12185","display_name":"Regulation and Compliance Studies","score":0.5597000122070312,"subfield":{"id":"https://openalex.org/subfields/1408","display_name":"Strategy and Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5593114495277405},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5267195701599121},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4588097333908081},{"id":"https://openalex.org/keywords/medical-waste","display_name":"Medical waste","score":0.45309311151504517},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43412742018699646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3993417024612427},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16995596885681152},{"id":"https://openalex.org/keywords/waste-management","display_name":"Waste management","score":0.12107712030410767}],"concepts":[{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5593114495277405},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5267195701599121},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4588097333908081},{"id":"https://openalex.org/C2992940845","wikidata":"https://www.wikidata.org/wiki/Q4915134","display_name":"Medical waste","level":2,"score":0.45309311151504517},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43412742018699646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3993417024612427},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16995596885681152},{"id":"https://openalex.org/C548081761","wikidata":"https://www.wikidata.org/wiki/Q180388","display_name":"Waste management","level":1,"score":0.12107712030410767}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cbms65348.2025.00181","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbms65348.2025.00181","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 38th International Symposium on Computer-Based Medical Systems (CBMS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W65738273","https://openalex.org/W121825459","https://openalex.org/W3010795489","https://openalex.org/W3130801746","https://openalex.org/W3132316130","https://openalex.org/W4387118812","https://openalex.org/W4407614203"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"The":[0,41,80,115,134,158],"identification":[1],"of":[2,45,111,163],"fraud,":[3,142],"waste,":[4,143],"and":[5,30,43,106,144,146,177],"abuse":[6,145],"in":[7,169],"healthcare":[8],"systems":[9],"is":[10,82],"critical":[11],"to":[12,33,53,66],"minimise":[13],"financial":[14],"losses":[15],"incurred":[16],"by":[17],"medical":[18,38,71,78,152,170],"aid":[19],"companies.":[20],"Traditional":[21],"fraud":[22,68,167],"detection":[23,69,91,168,179],"methods":[24],"are":[25],"based":[26],"on":[27,119,174],"manual":[28,175],"processes":[29],"often":[31],"fail":[32],"identify":[34],"hidden":[35],"patterns":[36],"within":[37],"claims":[39,72],"data.":[40],"complexity":[42],"scale":[44],"fraudulent":[46],"activities":[47],"require":[48],"more":[49],"advanced,":[50],"data-driven":[51],"approaches":[52],"detect.":[54],"This":[55],"paper":[56,159],"develops":[57],"a":[58,75,83],"framework":[59,81,139],"that":[60,86,137],"employs":[61,87],"unsupervised":[62,89,164],"machine":[63],"learning":[64,165],"models":[65],"improve":[67],"from":[70],"data":[73],"for":[74,166],"South":[76],"African":[77],"scheme.":[79],"two-layer":[84],"approach":[85],"six":[88],"anomaly":[90],"algorithms,":[92],"including":[93],"isolation":[94],"forest,":[95],"one-class":[96],"support":[97],"vector":[98],"machine,":[99],"autoencoder,":[100],"selforganising":[101],"map,":[102],"local":[103,131],"outlier":[104,132],"factor,":[105],"hierarchical":[107],"densitybased":[108],"spatial":[109],"clustering":[110],"applications":[112],"with":[113],"noise.":[114],"first":[116],"layer":[117,126],"focuses":[118],"detecting":[120],"global":[121],"outliers,":[122],"while":[123],"the":[124,138,161],"second":[125],"refines":[127],"these":[128],"classifications":[129],"using":[130],"factors.":[133],"results":[135],"show":[136],"flags":[140],"potential":[141,162],"provides":[147],"valuable":[148],"insights":[149],"into":[150],"which":[151],"practices":[153],"should":[154],"be":[155],"investigated":[156],"further.":[157],"highlights":[160],"claims,":[171],"reducing":[172],"reliance":[173],"audits":[176],"improving":[178],"accuracy.":[180]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}