{"id":"https://openalex.org/W4221163971","doi":"https://doi.org/10.1109/tnnls.2022.3183864","title":"Targeted-BEHRT: Deep Learning for Observational Causal Inference on Longitudinal Electronic Health Records","display_name":"Targeted-BEHRT: Deep Learning for Observational Causal Inference on Longitudinal Electronic Health Records","publication_year":2022,"publication_date":"2022-06-23","ids":{"openalex":"https://openalex.org/W4221163971","doi":"https://doi.org/10.1109/tnnls.2022.3183864","pmid":"https://pubmed.ncbi.nlm.nih.gov/35737602"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3183864","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3183864","pdf_url":"https://ieeexplore.ieee.org/ielx7/5962385/6104215/09804397.pdf","source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/5962385/6104215/09804397.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063293709","display_name":"Shishir Rao","orcid":"https://orcid.org/0000-0001-7331-9416"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Shishir Rao","raw_affiliation_strings":["Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K"],"raw_orcid":"https://orcid.org/0000-0001-7331-9416","affiliations":[{"raw_affiliation_string":"Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022241147","display_name":"Mohammad Mamouei","orcid":"https://orcid.org/0000-0002-7757-5238"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mohammad Mamouei","raw_affiliation_strings":["Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005615304","display_name":"Gholamreza Salimi\u2010Khorshidi","orcid":"https://orcid.org/0000-0002-4166-2858"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gholamreza Salimi-Khorshidi","raw_affiliation_strings":["Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102715557","display_name":"Yikuan Li","orcid":"https://orcid.org/0000-0001-9045-5786"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yikuan Li","raw_affiliation_strings":["Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K"],"raw_orcid":"https://orcid.org/0000-0001-9045-5786","affiliations":[{"raw_affiliation_string":"Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050806006","display_name":"Rema Ramakrishnan","orcid":"https://orcid.org/0000-0002-6784-8319"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Rema Ramakrishnan","raw_affiliation_strings":["National Perinatal Epidemiology Unit, University of Oxford, Oxford, U.K"],"raw_orcid":"https://orcid.org/0000-0002-6784-8319","affiliations":[{"raw_affiliation_string":"National Perinatal Epidemiology Unit, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057815334","display_name":"Abdel\u01ceali Hassa\u00efne","orcid":"https://orcid.org/0000-0002-3270-1165"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Abdelaali Hassaine","raw_affiliation_strings":["Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K"],"raw_orcid":"https://orcid.org/0000-0002-3270-1165","affiliations":[{"raw_affiliation_string":"Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049277133","display_name":"Dexter Canoy","orcid":"https://orcid.org/0000-0003-4493-9901"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Dexter Canoy","raw_affiliation_strings":["Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K","University of Oxford, Oxford, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149"]},{"raw_affiliation_string":"University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016617643","display_name":"Kazem Rahimi","orcid":"https://orcid.org/0000-0002-4807-4610"},"institutions":[{"id":"https://openalex.org/I40120149","display_name":"University of Oxford","ror":"https://ror.org/052gg0110","country_code":"GB","type":"education","lineage":["https://openalex.org/I40120149"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kazem Rahimi","raw_affiliation_strings":["Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K","University of Oxford, Oxford, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nuffield Department of Women’s & Reproductive Health, University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149"]},{"raw_affiliation_string":"University of Oxford, Oxford, U.K","institution_ids":["https://openalex.org/I40120149"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5063293709"],"corresponding_institution_ids":["https://openalex.org/I40120149"],"apc_list":null,"apc_paid":null,"fwci":4.7184,"has_fulltext":true,"cited_by_count":37,"citation_normalized_percentile":{"value":0.95391206,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"35","issue":"4","first_page":"5027","last_page":"5038"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9997000098228455,"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":0.9997000098228455,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/observational-study","display_name":"Observational study","score":0.784455418586731},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.7808641195297241},{"id":"https://openalex.org/keywords/health-records","display_name":"Health records","score":0.7608304619789124},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5765857100486755},{"id":"https://openalex.org/keywords/electronic-health-record","display_name":"Electronic health record","score":0.4863601326942444},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4409015476703644},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3964079022407532},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3747357428073883},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.36390402913093567},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3539392054080963},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.29592230916023254},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.23920685052871704},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.144747793674469},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12897947430610657},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.11155468225479126},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.09461164474487305}],"concepts":[{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.784455418586731},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.7808641195297241},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.7608304619789124},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5765857100486755},{"id":"https://openalex.org/C3020144179","wikidata":"https://www.wikidata.org/wiki/Q10871684","display_name":"Electronic health record","level":3,"score":0.4863601326942444},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4409015476703644},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3964079022407532},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3747357428073883},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.36390402913093567},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3539392054080963},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.29592230916023254},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.23920685052871704},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.144747793674469},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12897947430610657},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.11155468225479126},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.09461164474487305},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000959","descriptor_name":"Antihypertensive Agents","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000959","descriptor_name":"Antihypertensive Agents","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000959","descriptor_name":"Antihypertensive Agents","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000959","descriptor_name":"Antihypertensive Agents","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000959","descriptor_name":"Antihypertensive Agents","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000959","descriptor_name":"Antihypertensive Agents","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000959","descriptor_name":"Antihypertensive Agents","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":"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":"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":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"descriptor_ui":"D009369","descriptor_name":"Neoplasms","qualifier_ui":"Q000453","qualifier_name":"epidemiology","is_major_topic":true},{"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":"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":"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},{"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},{"descriptor_ui":"D057286","descriptor_name":"Electronic Health Records","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1109/tnnls.2022.3183864","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3183864","pdf_url":"https://ieeexplore.ieee.org/ielx7/5962385/6104215/09804397.pdf","source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35737602","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35737602","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 transactions on neural networks and learning systems","raw_type":null},{"id":"pmh:oai:eprints.ncl.ac.uk:287860","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402485","display_name":"Newcastle University ePrints (Newcastle Univesity)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I84884186","host_organization_name":"Newcastle University","host_organization_lineage":["https://openalex.org/I84884186"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""},{"id":"pmh:oai:ora.ox.ac.uk:uuid:42dca2d1-4e89-46de-83af-c30ccf68a63f","is_oa":true,"landing_page_url":"https://ora.ox.ac.uk/objects/uuid:42dca2d1-4e89-46de-83af-c30ccf68a63f","pdf_url":null,"source":{"id":"https://openalex.org/S4306402636","display_name":"Oxford University Research Archive (ORA) (University of Oxford)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40120149","host_organization_name":"University of Oxford","host_organization_lineage":["https://openalex.org/I40120149"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symplectic Elements","raw_type":"Journal article"}],"best_oa_location":{"id":"doi:10.1109/tnnls.2022.3183864","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3183864","pdf_url":"https://ieeexplore.ieee.org/ielx7/5962385/6104215/09804397.pdf","source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7799999713897705,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G1047006668","display_name":null,"funder_award_id":"ES/P0110551/1","funder_id":"https://openalex.org/F4320319992","funder_display_name":"British Heart Foundation"},{"id":"https://openalex.org/G2598251462","display_name":null,"funder_award_id":"PG/18/65/33872","funder_id":"https://openalex.org/F4320319992","funder_display_name":"British Heart Foundation"},{"id":"https://openalex.org/G2738757250","display_name":null,"funder_award_id":"ES/P0110551/1","funder_id":"https://openalex.org/F4320314731","funder_display_name":"UK Research and Innovation"},{"id":"https://openalex.org/G521829944","display_name":null,"funder_award_id":"FS/PhD/21/29110","funder_id":"https://openalex.org/F4320319992","funder_display_name":"British Heart Foundation"}],"funders":[{"id":"https://openalex.org/F4320314731","display_name":"UK Research and Innovation","ror":"https://ror.org/001aqnf71"},{"id":"https://openalex.org/F4320319990","display_name":"National Institute for Health and Care Research","ror":"https://ror.org/0187kwz08"},{"id":"https://openalex.org/F4320319992","display_name":"British Heart Foundation","ror":"https://ror.org/02wdwnk04"},{"id":"https://openalex.org/F4320319994","display_name":"Department of Health and Social Care","ror":"https://ror.org/03sbpja79"},{"id":"https://openalex.org/F4320320290","display_name":"University of Oxford","ror":"https://ror.org/052gg0110"},{"id":"https://openalex.org/F4320331674","display_name":"Global Challenges Research Fund","ror":null},{"id":"https://openalex.org/F4320334902","display_name":"Oxford Martin School, University of Oxford","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4221163971.pdf","grobid_xml":"https://content.openalex.org/works/W4221163971.grobid-xml"},"referenced_works_count":64,"referenced_works":["https://openalex.org/W1516659296","https://openalex.org/W1986817546","https://openalex.org/W1990538023","https://openalex.org/W2009187570","https://openalex.org/W2012116377","https://openalex.org/W2022450888","https://openalex.org/W2051227550","https://openalex.org/W2066443416","https://openalex.org/W2071618848","https://openalex.org/W2119852447","https://openalex.org/W2126292488","https://openalex.org/W2140319788","https://openalex.org/W2144113585","https://openalex.org/W2144387798","https://openalex.org/W2150291618","https://openalex.org/W2171074980","https://openalex.org/W2171427509","https://openalex.org/W2481271618","https://openalex.org/W2566529584","https://openalex.org/W2602904671","https://openalex.org/W2605397892","https://openalex.org/W2761665523","https://openalex.org/W2791794153","https://openalex.org/W2802284801","https://openalex.org/W2804604520","https://openalex.org/W2804823968","https://openalex.org/W2883724551","https://openalex.org/W2896457183","https://openalex.org/W2936671417","https://openalex.org/W2938572117","https://openalex.org/W2949417153","https://openalex.org/W2962929144","https://openalex.org/W2963919224","https://openalex.org/W2970278855","https://openalex.org/W2970933040","https://openalex.org/W3017637887","https://openalex.org/W3047300725","https://openalex.org/W3123436326","https://openalex.org/W3125218497","https://openalex.org/W3145416765","https://openalex.org/W3173569500","https://openalex.org/W4248240383","https://openalex.org/W4286976645","https://openalex.org/W4287902487","https://openalex.org/W4289293786","https://openalex.org/W4295312788","https://openalex.org/W6631190155","https://openalex.org/W6729580568","https://openalex.org/W6735632117","https://openalex.org/W6739095351","https://openalex.org/W6739901393","https://openalex.org/W6752178629","https://openalex.org/W6754197187","https://openalex.org/W6754821620","https://openalex.org/W6755207826","https://openalex.org/W6755887172","https://openalex.org/W6760742749","https://openalex.org/W6761394466","https://openalex.org/W6761561128","https://openalex.org/W6763480546","https://openalex.org/W6766978945","https://openalex.org/W6773392044","https://openalex.org/W6781965151","https://openalex.org/W6801541938"],"related_works":["https://openalex.org/W2979832559","https://openalex.org/W3128129045","https://openalex.org/W4324300609","https://openalex.org/W4387531643","https://openalex.org/W4385077270","https://openalex.org/W4396768342","https://openalex.org/W4231150422","https://openalex.org/W4400520609","https://openalex.org/W3164869265","https://openalex.org/W2997970376"],"abstract_inverted_index":{"Observational":[0],"causal":[1,26,62,75,80,125],"inference":[2,63,126],"is":[3,200],"useful":[4],"for":[5,44,61,124],"decision-making":[6],"in":[7,28,127],"medicine":[8],"when":[9],"randomized":[10],"clinical":[11],"trials":[12],"(RCTs)":[13],"are":[14],"infeasible":[15],"or":[16],"nongeneralizable.":[17],"However,":[18],"traditional":[19],"approaches":[20],"do":[21],"not":[22],"always":[23],"deliver":[24],"unconfounded":[25],"conclusions":[27],"practice.":[29],"The":[30],"rise":[31],"of":[32,41,48,77,84,86,133,141,150,159,171,192],"\"doubly":[33],"robust\"":[34],"nonparametric":[35],"tools":[36],"coupled":[37,102],"with":[38,103,136,183,202],"the":[39,82,148],"growth":[40],"deep":[42,121],"learning":[43,122],"capturing":[45],"rich":[46],"representations":[47],"multimodal":[49],"data":[50],"offers":[51],"a":[52,94],"unique":[53],"opportunity":[54],"to":[55,107,117,145],"develop":[56,93],"and":[57,120,139],"test":[58,147,154],"such":[59],"models":[60,123],"on":[64,88,130,157,196],"comprehensive":[65],"electronic":[66],"health":[67],"records":[68],"(EHRs).":[69],"In":[70,143],"this":[71],"article,":[72],"we":[73,153],"investigate":[74],"modeling":[76],"an":[78,190],"RCT-established":[79],"association:":[81],"effect":[83,195],"classes":[85],"antihypertensive":[87,194],"incident":[89],"cancer":[90,197],"risk.":[91],"We":[92,113,162],"transformer-based":[95],"model,":[96],"targeted":[97],"bidirectional":[98],"EHR":[99],"transformer":[100],"(T-BEHRT)":[101],"doubly":[104],"robust":[105],"estimation":[106],"estimate":[108,191],"average":[109],"risk":[110,173,198],"ratio":[111],"(RR).":[112],"compare":[114],"our":[115,134,151,155,165,187],"model":[116,156,166,188],"benchmark":[118,184],"statistical":[119],"multiple":[128],"experiments":[129],"semi-synthetic":[131],"derivations":[132],"dataset":[135],"various":[137],"types":[138],"intensities":[140],"confounding.":[142],"order":[144],"further":[146],"reliability":[149],"approach,":[152],"situations":[158],"limited":[160],"data.":[161],"find":[163],"that":[164,199],"provides":[167,189],"more":[168],"accurate":[169],"estimates":[170],"relative":[172],"[least":[174],"sum":[175],"absolute":[176],"error":[177],"(SAE)":[178],"from":[179,205],"ground":[180],"truth]":[181],"compared":[182],"estimations.":[185],"Finally,":[186],"class-wise":[193],"consistent":[201],"results":[203],"derived":[204],"RCTs.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-03T09:05:47.796612","created_date":"2025-10-10T00:00:00"}