{"id":"https://openalex.org/W4206528984","doi":"https://doi.org/10.1109/bibm52615.2021.9669367","title":"OA-MedSQL: Order-Aware Medical Sequence Learning for Clinical Outcome Prediction","display_name":"OA-MedSQL: Order-Aware Medical Sequence Learning for Clinical Outcome Prediction","publication_year":2021,"publication_date":"2021-12-09","ids":{"openalex":"https://openalex.org/W4206528984","doi":"https://doi.org/10.1109/bibm52615.2021.9669367"},"language":"en","primary_location":{"id":"doi:10.1109/bibm52615.2021.9669367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669367","pdf_url":null,"source":{"id":"https://openalex.org/S4363607735","display_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5000348675","display_name":"Tong Wu","orcid":"https://orcid.org/0000-0002-7474-6943"},"institutions":[{"id":"https://openalex.org/I4210108991","display_name":"IQVIA (United States)","ror":"https://ror.org/01mk44223","country_code":"US","type":"company","lineage":["https://openalex.org/I4210108991"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tong Wu","raw_affiliation_strings":["Advanced Analytics, IQVIA Inc., Plymouth Meeting, PA, USA"],"affiliations":[{"raw_affiliation_string":"Advanced Analytics, IQVIA Inc., Plymouth Meeting, PA, USA","institution_ids":["https://openalex.org/I4210108991"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100371984","display_name":"Yue Wang","orcid":"https://orcid.org/0000-0002-0278-2347"},"institutions":[{"id":"https://openalex.org/I4210108991","display_name":"IQVIA (United States)","ror":"https://ror.org/01mk44223","country_code":"US","type":"company","lineage":["https://openalex.org/I4210108991"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yue Wang","raw_affiliation_strings":["Advanced Analytics, IQVIA Inc., Plymouth Meeting, PA, USA"],"affiliations":[{"raw_affiliation_string":"Advanced Analytics, IQVIA Inc., Plymouth Meeting, PA, USA","institution_ids":["https://openalex.org/I4210108991"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100398996","display_name":"Yunlong Wang","orcid":"https://orcid.org/0000-0003-2186-9306"},"institutions":[{"id":"https://openalex.org/I4210108991","display_name":"IQVIA (United States)","ror":"https://ror.org/01mk44223","country_code":"US","type":"company","lineage":["https://openalex.org/I4210108991"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yunlong Wang","raw_affiliation_strings":["Advanced Analytics, IQVIA Inc., Plymouth Meeting, PA, USA"],"affiliations":[{"raw_affiliation_string":"Advanced Analytics, IQVIA Inc., Plymouth Meeting, PA, USA","institution_ids":["https://openalex.org/I4210108991"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103143539","display_name":"Emily Zhao","orcid":"https://orcid.org/0000-0002-4055-0774"},"institutions":[{"id":"https://openalex.org/I4210108991","display_name":"IQVIA (United States)","ror":"https://ror.org/01mk44223","country_code":"US","type":"company","lineage":["https://openalex.org/I4210108991"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Emily Zhao","raw_affiliation_strings":["Advanced Analytics, IQVIA Inc., Plymouth Meeting, PA, USA"],"affiliations":[{"raw_affiliation_string":"Advanced Analytics, IQVIA Inc., Plymouth Meeting, PA, USA","institution_ids":["https://openalex.org/I4210108991"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103086654","display_name":"Wang Gao","orcid":"https://orcid.org/0000-0002-3827-2111"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gao Wang","raw_affiliation_strings":["Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA"],"affiliations":[{"raw_affiliation_string":"Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5000348675"],"corresponding_institution_ids":["https://openalex.org/I4210108991"],"apc_list":null,"apc_paid":null,"fwci":0.1257,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40100953,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2013","issue":null,"first_page":"1585","last_page":"1589"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.996399998664856,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.996399998664856,"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/T10261","display_name":"Genetic Associations and Epidemiology","score":0.9632999897003174,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10027","display_name":"Diabetes, Cardiovascular Risks, and Lipoproteins","score":0.9577999711036682,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/milestone","display_name":"Milestone","score":0.7778517603874207},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7239209413528442},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6326375007629395},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6318489909172058},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6134287714958191},{"id":"https://openalex.org/keywords/sequence-learning","display_name":"Sequence learning","score":0.5814411640167236},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.57551509141922},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.49563419818878174},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.443853497505188},{"id":"https://openalex.org/keywords/medical-record","display_name":"Medical record","score":0.4152945876121521},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1528027355670929},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10271981358528137},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.0898306667804718}],"concepts":[{"id":"https://openalex.org/C120060458","wikidata":"https://www.wikidata.org/wiki/Q10145","display_name":"Milestone","level":2,"score":0.7778517603874207},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7239209413528442},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6326375007629395},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6318489909172058},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6134287714958191},{"id":"https://openalex.org/C40506919","wikidata":"https://www.wikidata.org/wiki/Q7452469","display_name":"Sequence learning","level":2,"score":0.5814411640167236},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.57551509141922},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.49563419818878174},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.443853497505188},{"id":"https://openalex.org/C195910791","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Medical record","level":2,"score":0.4152945876121521},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1528027355670929},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10271981358528137},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0898306667804718},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm52615.2021.9669367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669367","pdf_url":null,"source":{"id":"https://openalex.org/S4363607735","display_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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":25,"referenced_works":["https://openalex.org/W31739655","https://openalex.org/W122349615","https://openalex.org/W138083078","https://openalex.org/W1844110723","https://openalex.org/W1995125949","https://openalex.org/W2005464046","https://openalex.org/W2014577670","https://openalex.org/W2062584238","https://openalex.org/W2082802852","https://openalex.org/W2096546669","https://openalex.org/W2122475441","https://openalex.org/W2139146948","https://openalex.org/W2165817472","https://openalex.org/W2571956521","https://openalex.org/W2763115747","https://openalex.org/W2810292591","https://openalex.org/W2899178218","https://openalex.org/W2963271116","https://openalex.org/W4210983280","https://openalex.org/W4289373464","https://openalex.org/W6605550364","https://openalex.org/W6638677654","https://openalex.org/W6726186668","https://openalex.org/W6731594228","https://openalex.org/W6754880608"],"related_works":["https://openalex.org/W4387878404","https://openalex.org/W2584040191","https://openalex.org/W2561695978","https://openalex.org/W2922924512","https://openalex.org/W1950486549","https://openalex.org/W3133583653","https://openalex.org/W3140574787","https://openalex.org/W2990251955","https://openalex.org/W2064167013","https://openalex.org/W2490667451"],"abstract_inverted_index":{"Leveraging":[0],"large":[1],"amounts":[2],"of":[3,17,79,93,122,159,164],"longitudinal":[4],"electronic":[5],"health":[6],"records":[7],"(EHR)":[8],"data":[9],"has":[10],"shown":[11],"great":[12],"potentials":[13],"for":[14,127],"predicting":[15,123],"progression":[16],"various":[18,55],"diseases.":[19],"In":[20],"this":[21],"work,":[22],"we":[23],"proposed":[24,110],"a":[25,31,113,147],"deep":[26],"learning":[27,42],"algorithm":[28],"based":[29],"on":[30,112,119],"customized":[32],"Long":[33],"Short-Term":[34],"Memory":[35],"(LSTM)":[36],"model":[37,52,96],"with":[38,61],"built-in":[39],"temporal":[40,75,81,153],"sequence":[41],"mechanism,":[43],"named":[44],"as":[45],"Order-Aware":[46],"Medical":[47],"SeQuence":[48],"Learning":[49],"(OA-MedSQL).":[50],"The":[51,77],"can":[53,133],"predict":[54],"clinical":[56,165],"outcomes":[57],"from":[58],"EHR":[59,115],"sequences":[60,82,154],"competitive":[62,141],"accuracies,":[63],"meanwhile":[64],"automatically":[65],"distills":[66],"patient":[67,160],"medical":[68],"journeys":[69,161],"into":[70],"clinically":[71],"meaningful":[72],"and":[73,162],"relevant":[74],"sequences.":[76],"extraction":[78],"milestone":[80,152],"is":[83],"mainly":[84],"facilitated":[85],"by":[86],"enforcing":[87],"an":[88],"order":[89],"to":[90,150],"the":[91,94,109,120],"neurons":[92],"LSTM":[95],"when":[97],"updating":[98],"their":[99],"cell":[100],"states":[101],"at":[102],"each":[103],"time":[104],"step.":[105],"We":[106],"have":[107],"evaluated":[108],"approach":[111],"real-world":[114],"dataset":[116],"that":[117,155],"focuses":[118],"task":[121],"first-line":[124],"treatment":[125],"initiation":[126],"Waldenstr\u00f6m":[128],"Macroglobulinemia":[129],"(WM)":[130],"patients.":[131],"OA-MedSQL":[132,145],"achieve":[134],"comparable":[135],"or":[136],"better":[137],"performance":[138],"than":[139],"several":[140],"baseline":[142],"methods.":[143],"Furthermore,":[144],"offers":[146],"native":[148],"way":[149],"extract":[151],"are":[156],"both":[157],"explanatory":[158],"predictive":[163],"outcomes.":[166]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
