{"id":"https://openalex.org/W3089168780","doi":"https://doi.org/10.1109/jbhi.2021.3063721","title":"Bidirectional Representation Learning From Transformers Using Multimodal Electronic Health Record Data to Predict Depression","display_name":"Bidirectional Representation Learning From Transformers Using Multimodal Electronic Health Record Data to Predict Depression","publication_year":2021,"publication_date":"2021-03-04","ids":{"openalex":"https://openalex.org/W3089168780","doi":"https://doi.org/10.1109/jbhi.2021.3063721","mag":"3089168780","pmid":"https://pubmed.ncbi.nlm.nih.gov/33661740"},"language":"en","primary_location":{"id":"doi:10.1109/jbhi.2021.3063721","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2021.3063721","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2009.12656","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yiwen Meng","orcid":"https://orcid.org/0000-0001-8055-4510"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]},{"id":"https://openalex.org/I4210121124","display_name":"Computational Diagnostics (United States)","ror":"https://ror.org/02fv0rq89","country_code":"US","type":"company","lineage":["https://openalex.org/I4210121124"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiwen Meng","raw_affiliation_strings":["Computational Diagnostics Lab, Department of Radiological Sciences and the Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA"],"raw_orcid":"https://orcid.org/0000-0001-8055-4510","affiliations":[{"raw_affiliation_string":"Computational Diagnostics Lab, Department of Radiological Sciences and the Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765","https://openalex.org/I4210121124"]}]},{"author_position":"middle","author":{"id":null,"display_name":"William Speier","orcid":"https://orcid.org/0000-0002-0890-8684"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]},{"id":"https://openalex.org/I4210121124","display_name":"Computational Diagnostics (United States)","ror":"https://ror.org/02fv0rq89","country_code":"US","type":"company","lineage":["https://openalex.org/I4210121124"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"William Speier","raw_affiliation_strings":["Computational Diagnostics Lab, Department of Radiological Sciences and the Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-0890-8684","affiliations":[{"raw_affiliation_string":"Computational Diagnostics Lab, Department of Radiological Sciences and the Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765","https://openalex.org/I4210121124"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Michael K. Ong","orcid":"https://orcid.org/0000-0001-8530-7754"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael K. Ong","raw_affiliation_strings":["Department of Medicine, University of California Los Angeles, Los Angeles, CA, USA"],"raw_orcid":"https://orcid.org/0000-0001-8530-7754","affiliations":[{"raw_affiliation_string":"Department of Medicine, University of California Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":null,"display_name":"Corey W. Arnold","orcid":"https://orcid.org/0000-0002-4119-8143"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]},{"id":"https://openalex.org/I4210121124","display_name":"Computational Diagnostics (United States)","ror":"https://ror.org/02fv0rq89","country_code":"US","type":"company","lineage":["https://openalex.org/I4210121124"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Corey W. Arnold","raw_affiliation_strings":["Computational Diagnostics Lab, Department of Radiological Sciences, Department of Pathology and Laboratory Medicine, Department of Bioengineering, and the Department of Electrical and Computer Engineering, University of California Los Angeles, Los Angeles, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-4119-8143","affiliations":[{"raw_affiliation_string":"Computational Diagnostics Lab, Department of Radiological Sciences, Department of Pathology and Laboratory Medicine, Department of Bioengineering, and the Department of Electrical and Computer Engineering, University of California Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765","https://openalex.org/I4210121124"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.0553,"has_fulltext":false,"cited_by_count":124,"citation_normalized_percentile":{"value":0.98683177,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"25","issue":"8","first_page":"3121","last_page":"3129"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9641000032424927,"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":0.9641000032424927,"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/T12488","display_name":"Mental Health via Writing","score":0.007899999618530273,"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/T11519","display_name":"Digital Mental Health Interventions","score":0.004000000189989805,"subfield":{"id":"https://openalex.org/subfields/3202","display_name":"Applied 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/electronic-health-record","display_name":"Electronic health record","score":0.6413000226020813},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5450000166893005},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5205000042915344},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4756999909877777},{"id":"https://openalex.org/keywords/health-records","display_name":"Health records","score":0.47279998660087585},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.44200000166893005},{"id":"https://openalex.org/keywords/external-data-representation","display_name":"External Data Representation","score":0.43209999799728394},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.39890000224113464},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.38960000872612}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7091000080108643},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6517000198364258},{"id":"https://openalex.org/C3020144179","wikidata":"https://www.wikidata.org/wiki/Q10871684","display_name":"Electronic health record","level":3,"score":0.6413000226020813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6269000172615051},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5450000166893005},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5205000042915344},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4756999909877777},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.47279998660087585},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.44200000166893005},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.43209999799728394},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.39890000224113464},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38690000772476196},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.38690000772476196},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3785000145435333},{"id":"https://openalex.org/C2778058735","wikidata":"https://www.wikidata.org/wiki/Q4692253","display_name":"Aggregate data","level":2,"score":0.3749000132083893},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.357699990272522},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.35370001196861267},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3522000014781952},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.30790001153945923},{"id":"https://openalex.org/C63527458","wikidata":"https://www.wikidata.org/wiki/Q5133829","display_name":"Clinical decision support system","level":3,"score":0.30079999566078186},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.2985999882221222},{"id":"https://openalex.org/C45827449","wikidata":"https://www.wikidata.org/wiki/Q5270338","display_name":"Diagnosis code","level":3,"score":0.29190000891685486},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.26440000534057617},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.25600001215934753},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.25119999051094055}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003863","descriptor_name":"Depression","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D003863","descriptor_name":"Depression","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D003863","descriptor_name":"Depression","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016247","descriptor_name":"Information Storage and Retrieval","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016247","descriptor_name":"Information Storage and Retrieval","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016247","descriptor_name":"Information Storage and Retrieval","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1109/jbhi.2021.3063721","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jbhi.2021.3063721","pdf_url":null,"source":{"id":"https://openalex.org/S2495854775","display_name":"IEEE Journal of Biomedical and Health Informatics","issn_l":"2168-2194","issn":["2168-2194","2168-2208"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Biomedical and Health Informatics","raw_type":"journal-article"},{"id":"pmid:33661740","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33661740","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE journal of biomedical and health informatics","raw_type":null},{"id":"pmh:oai:arXiv.org:2009.12656","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.12656","pdf_url":"https://arxiv.org/pdf/2009.12656","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8606118","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8606118","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE J Biomed Health Inform","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2009.12656","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2009.12656","pdf_url":"https://arxiv.org/pdf/2009.12656","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4892333469","display_name":null,"funder_award_id":"NIH/NHLBI R01HL141773","funder_id":"https://openalex.org/F4320337338","funder_display_name":"National Heart, Lung, and Blood Institute"},{"id":"https://openalex.org/G8192869175","display_name":null,"funder_award_id":"R01 HL141773","funder_id":"https://openalex.org/F4320337338","funder_display_name":"National Heart, Lung, and Blood Institute"}],"funders":[{"id":"https://openalex.org/F4320337338","display_name":"National Heart, Lung, and Blood Institute","ror":"https://ror.org/012pb6c26"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1779612606","https://openalex.org/W1845587167","https://openalex.org/W1956509155","https://openalex.org/W1985329916","https://openalex.org/W2016127234","https://openalex.org/W2039056175","https://openalex.org/W2117539524","https://openalex.org/W2125674401","https://openalex.org/W2129330384","https://openalex.org/W2134431612","https://openalex.org/W2174344915","https://openalex.org/W2216133675","https://openalex.org/W2343760456","https://openalex.org/W2587860706","https://openalex.org/W2611715281","https://openalex.org/W2625625371","https://openalex.org/W2690721124","https://openalex.org/W2809396336","https://openalex.org/W2912654919","https://openalex.org/W2951704914","https://openalex.org/W2964006392","https://openalex.org/W2997494090","https://openalex.org/W3036914761","https://openalex.org/W6631190155","https://openalex.org/W6680930200","https://openalex.org/W6685764666","https://openalex.org/W6685812147","https://openalex.org/W6726186668","https://openalex.org/W6738631160","https://openalex.org/W6739651123","https://openalex.org/W6739901393","https://openalex.org/W6754497374","https://openalex.org/W6755207826","https://openalex.org/W6765671411","https://openalex.org/W6773649962","https://openalex.org/W6778642046"],"related_works":[],"abstract_inverted_index":{"Advancements":[0],"in":[1,91,120,133,153,166,210],"machine":[2],"learning":[3,53,59],"algorithms":[4],"have":[5],"had":[6],"a":[7,50,64,92],"beneficial":[8],"impact":[9],"on":[10,29,60,112],"representation":[11,58],"learning,":[12],"classification,":[13],"and":[14,81,88,110,124,200,217],"prediction":[15,98,101,155],"models":[16],"built":[17],"using":[18],"electronic":[19],"health":[20],"record":[21],"(EHR)":[22],"data.":[23],"Effort":[24],"has":[25],"been":[26],"put":[27],"both":[28],"increasing":[30],"models'":[31],"overall":[32],"performance":[33],"as":[34,36],"well":[35],"improving":[37],"their":[38],"interpretability,":[39,201],"particularly":[40],"regarding":[41],"the":[42,86,105,117,127,134,139,146,158,163,171,179,185,211],"decision-making":[43],"process.":[44],"In":[45],"this":[46],"study,":[47],"we":[48],"present":[49],"temporal":[51,93],"deep":[52],"model":[54,74,137],"to":[55,67,77,115,125,151,157,188,193],"perform":[56],"bidirectional":[57],"EHR":[61,87,113,131,191],"sequences":[62],"with":[63],"transformer":[65],"architecture":[66],"predict":[68,194],"future":[69,212],"diagnosis":[70],"of":[71,108,142],"depression.":[72],"This":[73],"is":[75],"able":[76],"aggregate":[78],"five":[79],"heterogenous":[80],"high-dimensional":[82],"data":[83,114,192],"sources":[84],"from":[85,149],"process":[89],"them":[90],"manner":[94],"for":[95,213],"chronic":[96,121,214],"disease":[97,122,215],"at":[99],"various":[100,175],"windows.":[102],"We":[103],"applied":[104],"current":[106,118],"trend":[107],"pretraining":[109],"fine-tuning":[111],"outperform":[116],"state-of-the-art":[119],"prediction,":[123],"demonstrate":[126,184],"underlying":[128],"relation":[129],"between":[130,174],"codes":[132],"sequence.":[135],"The":[136],"generated":[138],"highest":[140],"increases":[141],"precision-recall":[143],"area":[144],"under":[145],"curve":[147],"(PRAUC)":[148],"0.70":[150],"0.76":[152],"depression":[154,195],"compared":[156],"best":[159],"baseline":[160],"model.":[161],"Furthermore,":[162],"self-attention":[164],"weights":[165],"each":[167],"sequence":[168],"quantitatively":[169],"demonstrated":[170],"inner":[172],"relationship":[173],"codes,":[176],"which":[177,202],"improved":[178],"model's":[180,186],"interpretability.":[181],"These":[182],"results":[183],"ability":[187],"utilize":[189],"heterogeneous":[190],"while":[196],"achieving":[197],"high":[198],"accuracy":[199],"may":[203],"facilitate":[204],"constructing":[205],"clinical":[206],"decision":[207],"support":[208],"systems":[209],"screening":[216],"early":[218],"detection.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":39},{"year":2023,"cited_by_count":30},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2020-10-01T00:00:00"}