{"id":"https://openalex.org/W4308381021","doi":"https://doi.org/10.1093/jamia/ocac212","title":"Using similar patients to predict complication in patients with diabetes, hypertension, and lipid disorder: a domain knowledge-infused convolutional neural network approach","display_name":"Using similar patients to predict complication in patients with diabetes, hypertension, and lipid disorder: a domain knowledge-infused convolutional neural network approach","publication_year":2022,"publication_date":"2022-11-07","ids":{"openalex":"https://openalex.org/W4308381021","doi":"https://doi.org/10.1093/jamia/ocac212","pmid":"https://pubmed.ncbi.nlm.nih.gov/36343096"},"language":"en","primary_location":{"id":"doi:10.1093/jamia/ocac212","is_oa":true,"landing_page_url":"https://doi.org/10.1093/jamia/ocac212","pdf_url":"https://academic.oup.com/jamia/article-pdf/30/2/273/48754896/ocac212.pdf","source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://academic.oup.com/jamia/article-pdf/30/2/273/48754896/ocac212.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010779961","display_name":"Ronald Wihal Oei","orcid":"https://orcid.org/0000-0003-3435-3421"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Ronald Wihal Oei","raw_affiliation_strings":["Institute of Data Science, National University of Singapore , Singapore"],"raw_orcid":"https://orcid.org/0000-0003-3435-3421","affiliations":[{"raw_affiliation_string":"Institute of Data Science, National University of Singapore , Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051209739","display_name":"Wynne Hsu","orcid":"https://orcid.org/0000-0002-4142-8893"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Wynne Hsu","raw_affiliation_strings":["Institute of Data Science, National University of Singapore , Singapore","School of Computing, National University of Singapore , Singapore"],"raw_orcid":"https://orcid.org/0000-0002-4142-8893","affiliations":[{"raw_affiliation_string":"Institute of Data Science, National University of Singapore , Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"School of Computing, National University of Singapore , Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019988958","display_name":"Mong Li Lee","orcid":"https://orcid.org/0000-0002-9636-388X"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Mong Li Lee","raw_affiliation_strings":["Institute of Data Science, National University of Singapore , Singapore","School of Computing, National University of Singapore , Singapore"],"raw_orcid":"https://orcid.org/0000-0002-9636-388X","affiliations":[{"raw_affiliation_string":"Institute of Data Science, National University of Singapore , Singapore","institution_ids":["https://openalex.org/I165932596"]},{"raw_affiliation_string":"School of Computing, National University of Singapore , Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016087648","display_name":"Ngiap Chuan Tan","orcid":"https://orcid.org/0000-0002-5946-1149"},"institutions":[{"id":"https://openalex.org/I4210113223","display_name":"SingHealth Polyclinics","ror":"https://ror.org/01ytv0571","country_code":"SG","type":"healthcare","lineage":["https://openalex.org/I4210113223"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Ngiap Chuan Tan","raw_affiliation_strings":["SingHealth Polyclinics, SingHealth , Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SingHealth Polyclinics, SingHealth , Singapore","institution_ids":["https://openalex.org/I4210113223"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5010779961"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":{"value":3967,"currency":"USD","value_usd":3967},"apc_paid":{"value":3967,"currency":"USD","value_usd":3967},"fwci":0.3852,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.68888889,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"30","issue":"2","first_page":"273","last_page":"281"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.7659000158309937,"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":0.7659000158309937,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.031599998474121094,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.017899999395012856,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7593759894371033},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6352416276931763},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6146101951599121},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.576170802116394},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49419835209846497},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4712046980857849},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4616829752922058},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4390834867954254},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4072634279727936},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3768535852432251},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.33696335554122925},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08229261636734009}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7593759894371033},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6352416276931763},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6146101951599121},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.576170802116394},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49419835209846497},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4712046980857849},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4616829752922058},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4390834867954254},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4072634279727936},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3768535852432251},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.33696335554122925},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08229261636734009},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D003920","descriptor_name":"Diabetes Mellitus","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003920","descriptor_name":"Diabetes Mellitus","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003920","descriptor_name":"Diabetes Mellitus","qualifier_ui":null,"qualifier_name":null,"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":"D006973","descriptor_name":"Hypertension","qualifier_ui":"Q000150","qualifier_name":"complications","is_major_topic":true},{"descriptor_ui":"D006973","descriptor_name":"Hypertension","qualifier_ui":"Q000150","qualifier_name":"complications","is_major_topic":true},{"descriptor_ui":"D006973","descriptor_name":"Hypertension","qualifier_ui":"Q000150","qualifier_name":"complications","is_major_topic":true},{"descriptor_ui":"D008055","descriptor_name":"Lipids","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008055","descriptor_name":"Lipids","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008055","descriptor_name":"Lipids","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","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":false},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","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":false}],"locations_count":3,"locations":[{"id":"doi:10.1093/jamia/ocac212","is_oa":true,"landing_page_url":"https://doi.org/10.1093/jamia/ocac212","pdf_url":"https://academic.oup.com/jamia/article-pdf/30/2/273/48754896/ocac212.pdf","source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},{"id":"pmid:36343096","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36343096","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":"Journal of the American Medical Informatics Association : JAMIA","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:9846687","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9846687","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Am Med Inform Assoc","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1093/jamia/ocac212","is_oa":true,"landing_page_url":"https://doi.org/10.1093/jamia/ocac212","pdf_url":"https://academic.oup.com/jamia/article-pdf/30/2/273/48754896/ocac212.pdf","source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.47999998927116394,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G4726863328","display_name":null,"funder_award_id":"AISG-GC-2019-001-2A","funder_id":"https://openalex.org/F4320320671","funder_display_name":"National Research Foundation"},{"id":"https://openalex.org/G5588925999","display_name":null,"funder_award_id":"AISG-GC-2019-001","funder_id":"https://openalex.org/F4320320709","funder_display_name":"National Research Foundation Singapore"},{"id":"https://openalex.org/G8667694176","display_name":null,"funder_award_id":"AISG-GC-2019-001-2A","funder_id":"https://openalex.org/F4320320709","funder_display_name":"National Research Foundation Singapore"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320320709","display_name":"National Research Foundation Singapore","ror":"https://ror.org/03cpyc314"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4308381021.pdf","grobid_xml":"https://content.openalex.org/works/W4308381021.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W29779864","https://openalex.org/W236448318","https://openalex.org/W1512511032","https://openalex.org/W2071628029","https://openalex.org/W2129832544","https://openalex.org/W2169715407","https://openalex.org/W2595226750","https://openalex.org/W2619881304","https://openalex.org/W2765127880","https://openalex.org/W2886951144","https://openalex.org/W2899736836","https://openalex.org/W2922429863","https://openalex.org/W2972869264","https://openalex.org/W2998530579","https://openalex.org/W3004465995","https://openalex.org/W3035640977","https://openalex.org/W3045670760","https://openalex.org/W3083654229","https://openalex.org/W3097720724","https://openalex.org/W3104823300","https://openalex.org/W3123974754","https://openalex.org/W3159925822","https://openalex.org/W3183289342","https://openalex.org/W4210758134","https://openalex.org/W4223552619","https://openalex.org/W4295312788","https://openalex.org/W6601200593","https://openalex.org/W6630833909","https://openalex.org/W6679504711","https://openalex.org/W6766978945"],"related_works":["https://openalex.org/W4311257506","https://openalex.org/W2337926734","https://openalex.org/W4319994054","https://openalex.org/W4366224123","https://openalex.org/W2963958939","https://openalex.org/W2793022090","https://openalex.org/W4320802194","https://openalex.org/W4298168912","https://openalex.org/W2919358988","https://openalex.org/W3173182854"],"abstract_inverted_index":{"OBJECTIVE:":[0],"This":[1],"study":[2,141],"aims":[3],"to":[4,25,78,94,101,108,147,215,224,230],"develop":[5],"a":[6,203,240],"convolutional":[7,15],"neural":[8,16],"network-based":[9],"learning":[10],"framework":[11],"called":[12],"domain":[13,68,118,209],"knowledge-infused":[14],"network":[17],"(DK-CNN)":[18],"for":[19,242,247],"retrieving":[20],"clinically":[21,149,217],"similar":[22,80,150,218,237],"patient":[23,212],"and":[24,70,89,130,152,178,211,233],"personalize":[26],"the":[27,33,41,96,154,180,185,189,231],"prediction":[28,92,172],"of":[29,45,73,98,170,236],"macrovascular":[30,90],"complication":[31,91,171],"using":[32],"retrieved":[34],"patients.":[35,81,219,248],"MATERIALS":[36],"AND":[37,199],"METHODS:":[38],"We":[39,82],"use":[40,83,117],"electronic":[42],"health":[43],"records":[44],"169":[46],"434":[47],"patients":[48,74,151,238],"with":[49,111,193],"diabetes,":[50],"hypertension,":[51],"and/or":[52],"lipid":[53],"disorder.":[54],"Patients":[55],"are":[56,106],"partitioned":[57],"into":[58],"7":[59,160,176],"subcohorts":[60],"based":[61],"on":[62],"their":[63],"comorbidities.":[64],"DK-CNN":[65,99,110,144,163,201],"integrates":[66],"both":[67],"knowledge":[69,119,210],"disease":[71],"trajectory":[72,132,213],"over":[75,133],"multiple":[76,134],"visits":[77],"retrieve":[79,148,216],"normalized":[84],"discounted":[85],"cumulative":[86],"gain":[87],"(nDCG)":[88],"performance":[93,173],"evaluate":[95],"effectiveness":[97],"compared":[100,192],"state-of-the-art":[102,166],"models.":[103,197],"Ablation":[104],"studies":[105,182],"conducted":[107],"compare":[109],"reduced":[112,196],"models":[113,123],"that":[114,124,184],"do":[115,125],"not":[116,126],"as":[120,122,239],"well":[121],"consider":[127],"short-term,":[128],"medium-term,":[129],"long-term":[131],"visits.":[135],"RESULTS:":[136],"Key":[137],"findings":[138],"from":[139],"this":[140],"are:":[142],"(1)":[143],"is":[145,202],"able":[146],"achieves":[153,188],"highest":[155,190],"nDCG":[156,191],"values":[157],"in":[158,168,174],"all":[159,175],"subcohorts;":[161,177],"(2)":[162],"outperforms":[164],"other":[165,194],"approaches":[167],"terms":[169],"(3)":[179],"ablation":[181],"show":[183],"full":[186],"model":[187],"2":[195],"DISCUSSION":[198],"CONCLUSIONS:":[200],"deep":[204],"learning-based":[205],"approach":[206],"which":[207],"incorporates":[208],"data":[214],"It":[220],"can":[221],"be":[222],"used":[223],"assist":[225],"physicians":[226],"who":[227],"may":[228],"refer":[229],"outcomes":[232],"past":[234],"treatments":[235],"guide":[241],"choosing":[243],"an":[244],"effective":[245],"treatment":[246]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}