{"id":"https://openalex.org/W4407129235","doi":"https://doi.org/10.1109/ieem62345.2024.10857131","title":"Evaluating Determinants of Health Insurance Premiums Using Advanced Multiple Linear Regression Techniques","display_name":"Evaluating Determinants of Health Insurance Premiums Using Advanced Multiple Linear Regression Techniques","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4407129235","doi":"https://doi.org/10.1109/ieem62345.2024.10857131"},"language":"en","primary_location":{"id":"doi:10.1109/ieem62345.2024.10857131","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem62345.2024.10857131","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","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/A5055548833","display_name":"Mariam Bader","orcid":"https://orcid.org/0009-0008-0219-5637"},"institutions":[{"id":"https://openalex.org/I176601375","display_name":"Khalifa University of Science and Technology","ror":"https://ror.org/05hffr360","country_code":"AE","type":"education","lineage":["https://openalex.org/I176601375"]}],"countries":["AE"],"is_corresponding":true,"raw_author_name":"Mariam Bader","raw_affiliation_strings":["Khalifa University,Department of Management Science and Engineering,Abu Dhabi,UAE"],"affiliations":[{"raw_affiliation_string":"Khalifa University,Department of Management Science and Engineering,Abu Dhabi,UAE","institution_ids":["https://openalex.org/I176601375"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082558192","display_name":"Maher Maalouf","orcid":"https://orcid.org/0000-0003-0516-6870"},"institutions":[{"id":"https://openalex.org/I176601375","display_name":"Khalifa University of Science and Technology","ror":"https://ror.org/05hffr360","country_code":"AE","type":"education","lineage":["https://openalex.org/I176601375"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Maher Maalouf","raw_affiliation_strings":["Khalifa University,Department of Management Science and Engineering,Abu Dhabi,UAE"],"affiliations":[{"raw_affiliation_string":"Khalifa University,Department of Management Science and Engineering,Abu Dhabi,UAE","institution_ids":["https://openalex.org/I176601375"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5055548833"],"corresponding_institution_ids":["https://openalex.org/I176601375"],"apc_list":null,"apc_paid":null,"fwci":1.0348,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.88819479,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"440","last_page":"444"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12394","display_name":"Insurance and Financial Risk Management","score":0.5245000123977661,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12394","display_name":"Insurance and Financial Risk Management","score":0.5245000123977661,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.5857887864112854},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4494169354438782},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.44851920008659363},{"id":"https://openalex.org/keywords/health-insurance","display_name":"Health insurance","score":0.4339751601219177},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4191031754016876},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3925139904022217},{"id":"https://openalex.org/keywords/actuarial-science","display_name":"Actuarial science","score":0.3856084942817688},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3073665499687195},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.2686420679092407},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.1772094964981079},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.16822975873947144},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16127493977546692},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16077455878257751}],"concepts":[{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5857887864112854},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4494169354438782},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44851920008659363},{"id":"https://openalex.org/C2983635472","wikidata":"https://www.wikidata.org/wiki/Q334911","display_name":"Health insurance","level":3,"score":0.4339751601219177},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4191031754016876},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3925139904022217},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.3856084942817688},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3073665499687195},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.2686420679092407},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.1772094964981079},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.16822975873947144},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16127493977546692},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16077455878257751},{"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:10.1109/ieem62345.2024.10857131","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem62345.2024.10857131","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5299999713897705,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2487770199","https://openalex.org/W3194858712","https://openalex.org/W3211260820","https://openalex.org/W4200115803","https://openalex.org/W4210954520","https://openalex.org/W4280528205"],"related_works":["https://openalex.org/W2610868774","https://openalex.org/W4399767649","https://openalex.org/W2092994918","https://openalex.org/W3216594821","https://openalex.org/W2390006526","https://openalex.org/W31220157","https://openalex.org/W4363647291","https://openalex.org/W1915333409","https://openalex.org/W2393341384","https://openalex.org/W2312753042"],"abstract_inverted_index":{"The":[0,64,178,203],"decision":[1],"to":[2,11,22,54,115,206,224],"purchase":[3],"health":[4,29,102,171,188],"insurance":[5,30,172,189,222],"policies":[6],"is":[7,119,134],"a":[8,121,207,226],"common":[9],"strategy":[10],"manage":[12],"the":[13,25,56,99,110,129,135,143,146,154,166,201,211],"escalating":[14],"costs":[15,173,219],"of":[16,35,79,92,101,124,161,210],"medical":[17],"treatment.":[18],"This":[19],"study":[20],"aims":[21],"statistically":[23],"identify":[24],"key":[26,212],"factors":[27,69,199],"determining":[28],"premium":[31,62],"prices.":[32],"A":[33],"variety":[34],"methods":[36,147],"were":[37],"applied,":[38],"including":[39],"Ordinary":[40],"Least":[41],"Square":[42,158],"Regression":[43,52,151],"(OLS),":[44],"Ridge":[45],"Regression,":[46,48],"Lasso":[47],"and":[49,83,94,137,139,197,220],"Support":[50,149],"Vector":[51,150],"(SVR),":[53],"determine":[55],"most":[57],"suitable":[58],"model":[59],"for":[60,169,186,230],"predicting":[61,170],"costs.":[63],"analysis":[65,86],"focused":[66],"on":[67,175],"multiple":[68],"such":[70],"as":[71,182],"age,":[72,89],"gender,":[73],"Body":[74],"Mass":[75],"Index":[76],"(BMI),":[77],"number":[78,91],"children,":[80,93],"smoking":[81,95],"status,":[82],"region.":[84],"OSL":[85],"revealed":[87],"that":[88,109,214],"BMI,":[90],"status":[96,127],"positively":[97],"affect":[98],"value":[100],"insurance.":[103],"Also,":[104],"it":[105,164],"has":[106,128],"been":[107],"shown":[108],"prices":[111],"vary":[112],"with":[113],"respect":[114],"regions,":[116],"while":[117,132],"gender":[118],"not":[120],"significant":[122],"determinant":[123],"charge.":[125],"Smoking":[126],"highest":[130],"impact,":[131],"age":[133],"least,":[136],"BMI":[138],"region":[140],"are":[141],"almost":[142],"same.":[144],"Among":[145],"tested,":[148],"(SVR)":[152],"demonstrated":[153],"lowest":[155],"Root":[156],"Mean":[157],"Error":[159],"(RMSE)":[160],"0.84,":[162],"indicating":[163],"provided":[165],"best":[167],"fit":[168],"based":[174],"these":[176],"variables.":[177],"findings":[179],"highlight":[180],"SVR":[181],"an":[183],"effective":[184],"tool":[185,229],"estimating":[187],"premiums,":[190],"offering":[191],"insights":[192],"into":[193],"how":[194],"various":[195],"personal":[196],"demographic":[198],"influence":[200],"cost.":[202],"results":[204],"contribute":[205],"deeper":[208],"understanding":[209],"drivers":[213],"help":[215],"customers":[216],"anticipate":[217],"future":[218],"allow":[221],"companies":[223],"adopt":[225],"more":[227,232],"precise":[228],"pricing":[231],"tailored,":[233],"data-driven":[234],"premiums.":[235]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
