{"id":"https://openalex.org/W3005436816","doi":"https://doi.org/10.1109/bibm47256.2019.8982975","title":"Predictive Modeling of Depression with a Large Claim Dataset","display_name":"Predictive Modeling of Depression with a Large Claim Dataset","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3005436816","doi":"https://doi.org/10.1109/bibm47256.2019.8982975","mag":"3005436816"},"language":"en","primary_location":{"id":"doi:10.1109/bibm47256.2019.8982975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm47256.2019.8982975","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5040015512","display_name":"Riyi Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I1318611468","display_name":"Fidelity Investments (United States)","ror":"https://ror.org/04v8c9r98","country_code":"US","type":"company","lineage":["https://openalex.org/I1318611468"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Riyi Qiu","raw_affiliation_strings":["Fidelity Investments,Boston,MA,USA","Fidelity Investments, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fidelity Investments,Boston,MA,USA","institution_ids":["https://openalex.org/I1318611468"]},{"raw_affiliation_string":"Fidelity Investments, Boston, MA, USA","institution_ids":["https://openalex.org/I1318611468"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000439830","display_name":"Vasu Kodali","orcid":null},"institutions":[{"id":"https://openalex.org/I1318611468","display_name":"Fidelity Investments (United States)","ror":"https://ror.org/04v8c9r98","country_code":"US","type":"company","lineage":["https://openalex.org/I1318611468"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vasu Kodali","raw_affiliation_strings":["Fidelity Investments,Boston,MA,USA","Fidelity Investments, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fidelity Investments,Boston,MA,USA","institution_ids":["https://openalex.org/I1318611468"]},{"raw_affiliation_string":"Fidelity Investments, Boston, MA, USA","institution_ids":["https://openalex.org/I1318611468"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104089725","display_name":"Mark Homer","orcid":null},"institutions":[{"id":"https://openalex.org/I1318611468","display_name":"Fidelity Investments (United States)","ror":"https://ror.org/04v8c9r98","country_code":"US","type":"company","lineage":["https://openalex.org/I1318611468"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mark Homer","raw_affiliation_strings":["Fidelity Investments,Boston,MA,USA","Fidelity Investments, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fidelity Investments,Boston,MA,USA","institution_ids":["https://openalex.org/I1318611468"]},{"raw_affiliation_string":"Fidelity Investments, Boston, MA, USA","institution_ids":["https://openalex.org/I1318611468"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100686019","display_name":"Andrew C. Heath","orcid":"https://orcid.org/0000-0002-9414-6857"},"institutions":[{"id":"https://openalex.org/I1318611468","display_name":"Fidelity Investments (United States)","ror":"https://ror.org/04v8c9r98","country_code":"US","type":"company","lineage":["https://openalex.org/I1318611468"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Heath","raw_affiliation_strings":["Fidelity Investments,Boston,MA,USA","Fidelity Investments, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fidelity Investments,Boston,MA,USA","institution_ids":["https://openalex.org/I1318611468"]},{"raw_affiliation_string":"Fidelity Investments, Boston, MA, USA","institution_ids":["https://openalex.org/I1318611468"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088570880","display_name":"Zhaoqi Wu","orcid":"https://orcid.org/0000-0001-7857-2875"},"institutions":[{"id":"https://openalex.org/I1318611468","display_name":"Fidelity Investments (United States)","ror":"https://ror.org/04v8c9r98","country_code":"US","type":"company","lineage":["https://openalex.org/I1318611468"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaoqi Wu","raw_affiliation_strings":["Fidelity Investments,Boston,MA,USA","Fidelity Investments, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fidelity Investments,Boston,MA,USA","institution_ids":["https://openalex.org/I1318611468"]},{"raw_affiliation_string":"Fidelity Investments, Boston, MA, USA","institution_ids":["https://openalex.org/I1318611468"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079756542","display_name":"Yugang Jia","orcid":"https://orcid.org/0009-0008-0628-5461"},"institutions":[{"id":"https://openalex.org/I1318611468","display_name":"Fidelity Investments (United States)","ror":"https://ror.org/04v8c9r98","country_code":"US","type":"company","lineage":["https://openalex.org/I1318611468"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yugang Jia","raw_affiliation_strings":["Fidelity Investments,Boston,MA,USA","Fidelity Investments, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fidelity Investments,Boston,MA,USA","institution_ids":["https://openalex.org/I1318611468"]},{"raw_affiliation_string":"Fidelity Investments, Boston, MA, USA","institution_ids":["https://openalex.org/I1318611468"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1318611468"],"apc_list":null,"apc_paid":null,"fwci":0.267,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.68084863,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1589","last_page":"1595"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.9610000252723694,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.9610000252723694,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13283","display_name":"Mental Health Research Topics","score":0.9433000087738037,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10272","display_name":"Mental Health Treatment and Access","score":0.9376000165939331,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7569558620452881},{"id":"https://openalex.org/keywords/depression","display_name":"Depression (economics)","score":0.6171801090240479},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.5584281086921692},{"id":"https://openalex.org/keywords/mental-health","display_name":"Mental health","score":0.4886394143104553},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4555134177207947},{"id":"https://openalex.org/keywords/medical-diagnosis","display_name":"Medical diagnosis","score":0.45145922899246216},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.44113123416900635},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.43552541732788086},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.42079228162765503},{"id":"https://openalex.org/keywords/intervention","display_name":"Intervention (counseling)","score":0.4116875231266022},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.40902945399284363},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4048612713813782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3804095983505249},{"id":"https://openalex.org/keywords/actuarial-science","display_name":"Actuarial science","score":0.37738850712776184},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3488600254058838},{"id":"https://openalex.org/keywords/psychiatry","display_name":"Psychiatry","score":0.3122459053993225},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.2202284336090088},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.13202044367790222},{"id":"https://openalex.org/keywords/environmental-health","display_name":"Environmental health","score":0.12391906976699829}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7569558620452881},{"id":"https://openalex.org/C2776867660","wikidata":"https://www.wikidata.org/wiki/Q1814941","display_name":"Depression (economics)","level":2,"score":0.6171801090240479},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.5584281086921692},{"id":"https://openalex.org/C134362201","wikidata":"https://www.wikidata.org/wiki/Q317309","display_name":"Mental health","level":2,"score":0.4886394143104553},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4555134177207947},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.45145922899246216},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.44113123416900635},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.43552541732788086},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.42079228162765503},{"id":"https://openalex.org/C2780665704","wikidata":"https://www.wikidata.org/wiki/Q959298","display_name":"Intervention (counseling)","level":2,"score":0.4116875231266022},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.40902945399284363},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4048612713813782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3804095983505249},{"id":"https://openalex.org/C162118730","wikidata":"https://www.wikidata.org/wiki/Q1128453","display_name":"Actuarial science","level":1,"score":0.37738850712776184},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3488600254058838},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.3122459053993225},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.2202284336090088},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.13202044367790222},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.12391906976699829},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm47256.2019.8982975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm47256.2019.8982975","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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":60,"referenced_works":["https://openalex.org/W8566840","https://openalex.org/W68662127","https://openalex.org/W1491401763","https://openalex.org/W1504483181","https://openalex.org/W1520487826","https://openalex.org/W1554944532","https://openalex.org/W1813097494","https://openalex.org/W1859721809","https://openalex.org/W1956509155","https://openalex.org/W1963678524","https://openalex.org/W1972087888","https://openalex.org/W1974618278","https://openalex.org/W1984476682","https://openalex.org/W1993155490","https://openalex.org/W2007095036","https://openalex.org/W2012258845","https://openalex.org/W2017930909","https://openalex.org/W2018829442","https://openalex.org/W2022783408","https://openalex.org/W2022997917","https://openalex.org/W2026839049","https://openalex.org/W2027677646","https://openalex.org/W2027845654","https://openalex.org/W2038081872","https://openalex.org/W2039056175","https://openalex.org/W2040367735","https://openalex.org/W2048089018","https://openalex.org/W2054985002","https://openalex.org/W2063847387","https://openalex.org/W2067054031","https://openalex.org/W2074086648","https://openalex.org/W2078379767","https://openalex.org/W2078959207","https://openalex.org/W2088153266","https://openalex.org/W2091083389","https://openalex.org/W2092000722","https://openalex.org/W2096782637","https://openalex.org/W2099763923","https://openalex.org/W2103997793","https://openalex.org/W2105346851","https://openalex.org/W2106059289","https://openalex.org/W2109158135","https://openalex.org/W2123687745","https://openalex.org/W2125035146","https://openalex.org/W2135046866","https://openalex.org/W2144625619","https://openalex.org/W2147411503","https://openalex.org/W2147668737","https://openalex.org/W2158153963","https://openalex.org/W2285222531","https://openalex.org/W2734425405","https://openalex.org/W2746698216","https://openalex.org/W2802632078","https://openalex.org/W4232165845","https://openalex.org/W4239013646","https://openalex.org/W4247809942","https://openalex.org/W4249733131","https://openalex.org/W4289800912","https://openalex.org/W4295845566","https://openalex.org/W6633362452"],"related_works":["https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W3171520305","https://openalex.org/W4256576576","https://openalex.org/W3135126032","https://openalex.org/W1924178503","https://openalex.org/W3191198889","https://openalex.org/W4399767560","https://openalex.org/W4399653172"],"abstract_inverted_index":{"Depression":[0],"has":[1],"been":[2],"a":[3,57,89,97,203],"major":[4],"concern":[5],"for":[6,30,81,210],"the":[7,21,44,76,104,135,140,146,196],"employers":[8,82],"due":[9],"to":[10,46,55,61,71,133,153],"its":[11],"high":[12],"prevalence":[13],"and":[14,26,40,73,108,120,124,168,175,205],"cost.":[15,86],"In":[16,50],"United":[17],"States,":[18],"6.8%":[19],"of":[20,91,137],"work":[22],"population":[23],"had":[24],"depression":[25,63,138,200],"it":[27],"is":[28,43,69,79,202],"accountable":[29],"over":[31,92],"$100":[32],"billion":[33],"workplace":[34],"loss":[35],"every":[36],"year.":[37,142],"Early":[38],"detection":[39],"timely":[41],"intervention":[42],"key":[45],"address":[47],"this":[48,51],"challenge.":[49],"paper,":[52],"we":[53],"proposed":[54],"leverage":[56],"large":[58],"claim":[59,77,197],"dataset":[60],"build":[62],"risk":[64],"prediction":[65,201],"model.":[66],"This":[67],"approach":[68],"easy":[70],"implement":[72],"scale":[74],"because":[75],"data":[78,132,198],"accessible":[80],"at":[83],"no":[84],"additional":[85],"We":[87,113,183,193],"derived":[88],"subset":[90],"7.2":[93],"million":[94],"patients":[95],"in":[96,139,190],"3-year":[98],"period,":[99],"with":[100,128],"2,099":[101],"variables":[102,158,187],"including":[103],"diagnosis,":[105],"procedure,":[106],"medication,":[107],"health":[109,165],"service":[110],"provider":[111],"information.":[112],"trained":[114],"two":[115,130],"models":[116,144],"(Least":[117],"Absolute":[118],"Shrinkage":[119],"Selection":[121],"Operator":[122],"(LASSO)":[123],"random":[125],"forest":[126],"*RF))":[127],"first":[129],"years":[131],"predict":[134],"onset":[136],"third":[141],"Both":[143],"achieved":[145],"best":[147],"comparable":[148],"performance":[149],"so":[150],"far":[151],"according":[152],"our":[154,161],"knowledge.":[155],"The":[156],"important":[157],"identified":[159],"by":[160,188],"algorithms":[162],"are":[163],"mental":[164],"related":[166],"medications":[167],"diagnoses":[169],"(other":[170],"than":[171],"depression),":[172],"gender":[173],"(female),":[174],"other":[176],"chronic":[177],"conditions":[178],"such":[179],"as":[180],"back":[181],"pain.":[182],"further":[184],"validated":[185],"these":[186],"confirming":[189],"clinical":[191],"literature.":[192],"concluded":[194],"that":[195],"based":[199],"viable":[204],"low":[206],"cost":[207],"approach,":[208],"especially":[209],"self-insured":[211],"employers.":[212]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}