{"id":"https://openalex.org/W4406947087","doi":"https://doi.org/10.1109/access.2025.3536479","title":"Efficient Handling of Data Imbalance in Health Insurance Fraud Detection Using Meta-Reinforcement Learning","display_name":"Efficient Handling of Data Imbalance in Health Insurance Fraud Detection Using Meta-Reinforcement Learning","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4406947087","doi":"https://doi.org/10.1109/access.2025.3536479"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3536479","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3536479","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.2025.3536479","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104208331","display_name":"Supriya Seshagiri","orcid":"https://orcid.org/0009-0000-2365-5702"},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Supriya Seshagiri","raw_affiliation_strings":["Department of Computer Science and Engineering, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India"],"raw_orcid":"https://orcid.org/0009-0000-2365-5702","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057241688","display_name":"K. V. Prema","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K. V. Prema","raw_affiliation_strings":["Department of Computer Science and Engineering, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India"],"raw_orcid":"https://orcid.org/0000-0002-8847-0749","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India","institution_ids":["https://openalex.org/I164861460"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I164861460"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":14.8573,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.98656955,"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":"23482","last_page":"23497"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9986000061035156,"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":0.9986000061035156,"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/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9092000126838684,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.7154865264892578},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6420744061470032},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.5538184642791748},{"id":"https://openalex.org/keywords/reinforcement","display_name":"Reinforcement","score":0.46847501397132874},{"id":"https://openalex.org/keywords/meta-analysis","display_name":"Meta-analysis","score":0.43665605783462524},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3847198188304901},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34980058670043945},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.08634445071220398},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.0730544924736023},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.061833739280700684}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7154865264892578},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6420744061470032},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.5538184642791748},{"id":"https://openalex.org/C67203356","wikidata":"https://www.wikidata.org/wiki/Q1321905","display_name":"Reinforcement","level":2,"score":0.46847501397132874},{"id":"https://openalex.org/C95190672","wikidata":"https://www.wikidata.org/wiki/Q815382","display_name":"Meta-analysis","level":2,"score":0.43665605783462524},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3847198188304901},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34980058670043945},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.08634445071220398},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0730544924736023},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.061833739280700684},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"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/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3536479","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3536479","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:67ab6eeaf329416aa5ccc347251c91d2","is_oa":true,"landing_page_url":"https://doaj.org/article/67ab6eeaf329416aa5ccc347251c91d2","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 23482-23497 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3536479","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3536479","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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W104535878","https://openalex.org/W134768651","https://openalex.org/W190483326","https://openalex.org/W316932473","https://openalex.org/W1635138928","https://openalex.org/W1993220166","https://openalex.org/W2025886727","https://openalex.org/W2080086724","https://openalex.org/W2104933073","https://openalex.org/W2118978333","https://openalex.org/W2338318698","https://openalex.org/W2548307244","https://openalex.org/W2562319768","https://openalex.org/W2614367549","https://openalex.org/W2800788706","https://openalex.org/W2892339005","https://openalex.org/W2903362744","https://openalex.org/W2905156999","https://openalex.org/W2963043696","https://openalex.org/W2971644666","https://openalex.org/W2991461464","https://openalex.org/W3001648619","https://openalex.org/W3009294386","https://openalex.org/W3011591403","https://openalex.org/W3019878896","https://openalex.org/W3119806474","https://openalex.org/W3137818553","https://openalex.org/W3154200785","https://openalex.org/W3163842339","https://openalex.org/W3173419192","https://openalex.org/W3198174103","https://openalex.org/W3198627383","https://openalex.org/W3202917770","https://openalex.org/W3206152519","https://openalex.org/W3208382680","https://openalex.org/W4214901712","https://openalex.org/W4225332015","https://openalex.org/W4236137412","https://openalex.org/W4243367342","https://openalex.org/W4281682128","https://openalex.org/W4285125814","https://openalex.org/W4297900628","https://openalex.org/W4360980173","https://openalex.org/W4361212625","https://openalex.org/W4365456882","https://openalex.org/W4378417908","https://openalex.org/W4386836946","https://openalex.org/W4389074726","https://openalex.org/W4391127911","https://openalex.org/W4392013674","https://openalex.org/W4394564350","https://openalex.org/W4395675278","https://openalex.org/W4398138776","https://openalex.org/W4398225848","https://openalex.org/W4401844715","https://openalex.org/W4402378055","https://openalex.org/W6729433768","https://openalex.org/W6731982132","https://openalex.org/W6762581443","https://openalex.org/W6779825901","https://openalex.org/W6785758868","https://openalex.org/W6796427662","https://openalex.org/W6804870611","https://openalex.org/W6838627330"],"related_works":["https://openalex.org/W4310083477","https://openalex.org/W2328553770","https://openalex.org/W4294873804","https://openalex.org/W4383109125","https://openalex.org/W2091347716","https://openalex.org/W98577079","https://openalex.org/W2891227010","https://openalex.org/W4319309271","https://openalex.org/W4313160267","https://openalex.org/W2548988175"],"abstract_inverted_index":{"Data":[0],"imbalance":[1,39,63,182,212],"is":[2,21,139,171],"one":[3],"of":[4,16,59,85,132,136,166,180,198],"the":[5,14,19,31,43,50,57,83,137,164,167,172,178],"major":[6],"challenges":[7],"in":[8,61,183],"health":[9,228],"insurance":[10,229],"fraud":[11,184,230],"detection":[12,231],"where":[13],"distribution":[15,109],"classes":[17],"within":[18],"dataset":[20],"significantly":[22],"skewed,":[23],"leading":[24],"statistical":[25],"models":[26,138],"to":[27,37,42,46,49,81,95,162,174,177,187,209,215],"be":[28,206,222],"biased":[29],"toward":[30],"dominant":[32],"class.":[33,52],"The":[34,134,196],"algorithmic":[35],"approaches":[36],"handling":[38],"involve":[40],"modification":[41,214],"loss":[44],"functions":[45,218],"sensitize":[47],"them":[48],"minor":[51],"Our":[53],"research":[54,170,200],"focuses":[55],"on":[56,115],"efficiency":[58,126,135],"meta-models":[60],"addressing":[62],"and":[64,99,110,121,127,149,154,190,219],"introduces":[65],"Meta-reinforcement":[66],"learning":[67,74],"(Meta-RL)":[68],"as":[69],"a":[70,188],"novel":[71],"solution":[72],"for":[73,129,193,227],"under":[75],"imbalance.":[76,133],"Meta-RL":[77,116,176,203],"leverages":[78],"meta-learning":[79],"principles":[80],"learn":[82,96],"characteristics":[84],"fraudulent":[86],"instances":[87],"dynamically.":[88],"This":[89,169],"adaptability":[90,128],"comes":[91],"from":[92],"its":[93],"ability":[94],"shared":[97],"representations":[98],"optimal":[100],"task-specific":[101],"strategies":[102],"using":[103,107,141],"limited":[104],"samples.":[105],"By":[106],"task":[108],"reward":[111],"shaping,":[112],"our":[113],"experiments":[114],"algorithms,":[117],"RL<sup":[118],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[119],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>,":[120],"VariBAD":[122],"achieve":[123],"superior":[124],"sample":[125],"varying":[130],"degrees":[131],"measured":[140],"imbalance-safe":[142],"metrics":[143,155],"like":[144,156],"Geometric":[145],"mean,":[146,148],"Harmonic":[147],"Mathew\u2019s":[150],"Correlation":[151],"Coefficient":[152],"(MCC),":[153],"Cohen\u2019s":[157],"Kappa":[158],"score":[159],"are":[160],"used":[161],"gauge":[163],"consistency":[165],"results.":[168],"first":[173],"apply":[175],"problem":[179],"data":[181,211],"detection,":[185],"contributing":[186],"generalizable":[189],"efficient":[191],"framework":[192],"imbalanced":[194],"learning.":[195],"findings":[197],"this":[199],"show":[201],"that":[202],"algorithms":[204],"can":[205,221],"effectively":[207],"tuned":[208],"handle":[210],"without":[213],"their":[216],"objective":[217],"hence,":[220],"considered":[223],"an":[224],"appropriate":[225],"option":[226],"solutions.":[232]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}