{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T04:02:23Z","timestamp":1774929743699,"version":"3.50.1"},"reference-count":43,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T00:00:00Z","timestamp":1763510400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U01TR003709"],"award-info":[{"award-number":["U01TR003709"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U24MH136069"],"award-info":[{"award-number":["U24MH136069"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U24AG098157"],"award-info":[{"award-number":["U24AG098157"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["RF1AG077820"],"award-info":[{"award-number":["RF1AG077820"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01AG073435"],"award-info":[{"award-number":["R01AG073435"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01LM013519"],"award-info":[{"award-number":["R01LM013519"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1R01LM014344"],"award-info":[{"award-number":["1R01LM014344"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01DK128237"],"award-info":[{"award-number":["R01DK128237"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R21AI167418"],"award-info":[{"award-number":["R21AI167418"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R21EY034179"],"award-info":[{"award-number":["R21EY034179"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>We propose Heterogeneity-aware Collaborative One-shot Lossless Algorithm for Generalized Linear Model (COLA-GLM-H), a novel one-shot lossless distributed algorithm that enables the integration of heterogeneous multi-institutional data while relying solely on instituion-level summary information rather than patient-level data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>Generalized Linear Models (GLMs) are widely used in medical research for analyzing diverse outcome types. In multi-institution settings, we demonstrated that the global likelihood can be reconstructed using only institution-level summary statistics, enabling lossless estimation without accessing individual records. We validated COLA-GLM-H in two real-world studies: (1) an emulated U.S. pediatric centralized network (719,383 patients) evaluating long-term cardiovascular risks following COVID-19, and (2) an internationally decentralized network of 120,429 hospitalized patients from seven databases across three countries assessing risk factors for COVID-19 mortality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In the centralized network, COLA-GLM-H produced estimates identical to those from pooled analyses. In the decentralized setting, the algorithm effectively integrated heterogeneous data across multiple clinical institutions using a single communication round.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>COLA-GLM-H provides a lossless, communication-efficient, and computation-efficient solution for multi-institutional research using only institution-level summary data. It accounts for between-institution heterogeneity and supports all outcome types within the exponential family, enabling secure, scalable, and accurate analysis in collaborative clinical research.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/jamia\/ocaf198","type":"journal-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T13:05:43Z","timestamp":1763125543000},"page":"700-709","source":"Crossref","is-referenced-by-count":1,"title":["A lossless one-shot distributed algorithm for addressing heterogeneity in multi-site generalized linear models"],"prefix":"10.1093","volume":"33","author":[{"given":"Bingyu","family":"Zhang","sequence":"first","affiliation":[{"name":"The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania , Philadelphia, PA 19104,","place":["United States"]},{"name":"The Graduate Group in Applied Mathematics and Computational Science, School of Arts and Sciences, University of Pennsylvania , Philadelphia, PA 19104,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiong","family":"Wu","sequence":"additional","affiliation":[{"name":"The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania , Philadelphia, PA 19104,","place":["United States"]},{"name":"Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine , Philadelphia, PA 19104,","place":["United States"]},{"name":"Department of Biostatistics and Health Data Science, University of Pittsburgh , Pittsburgh, PA 15261,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2970-0778","authenticated-orcid":false,"given":"Jenna M","family":"Reps","sequence":"additional","affiliation":[{"name":"Johnson & Johnson, Epidemiology , Titusville, NJ 08560,","place":["United States"]},{"name":"Department of Medical Informatics, Erasmus University Medical Center, 3000 CA Rotterdam,","place":["The Netherlands"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lu","family":"Li","sequence":"additional","affiliation":[{"name":"The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania , Philadelphia, PA 19104,","place":["United States"]},{"name":"The Graduate Group in Applied Mathematics and Computational Science, School of Arts and Sciences, University of Pennsylvania , Philadelphia, PA 19104,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiayi","family":"Tong","sequence":"additional","affiliation":[{"name":"The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania , Philadelphia, PA 19104,","place":["United States"]},{"name":"Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine , Philadelphia, PA 19104,","place":["United States"]},{"name":"Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health , Baltimore, MD 21205,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiwen","family":"Lu","sequence":"additional","affiliation":[{"name":"The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania , Philadelphia, PA 19104,","place":["United States"]},{"name":"The Graduate Group in Applied Mathematics and Computational Science, School of Arts and Sciences, University of Pennsylvania , Philadelphia, PA 19104,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1431-0785","authenticated-orcid":false,"given":"Dazheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania , Philadelphia, PA 19104,","place":["United States"]},{"name":"Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine , Philadelphia, PA 19104,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan Manuel","family":"Ramirez-Anguita","sequence":"additional","affiliation":[{"name":"Research Programme on Biomedical Informatics, Hospital del Mar, Hospital del Mar Research Institute (HMRIB) , 08003 Barcelona,","place":["Spain"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiang","family":"Bian","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Health Data Science, School of Medicine, Indiana University , Indianapolis, IN 46202,","place":["United States"]},{"name":"Regenstrief Institute , Indianapolis, IN 46202,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Milou T","family":"Brand","sequence":"additional","affiliation":[{"name":"Real World Solutions, IQVIA , Durham, NC 27703,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Falconer","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Columbia University , New York, NY 10032,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miguel A","family":"Mayer","sequence":"additional","affiliation":[{"name":"Research Programme on Biomedical Informatics, Hospital del Mar, Hospital del Mar Research Institute (HMRIB) , 08003 Barcelona,","place":["Spain"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7723-417X","authenticated-orcid":false,"given":"Ross D","family":"Williams","sequence":"additional","affiliation":[{"name":"Department of Medical Informatics, Erasmus University Medical Center, 3000 CA Rotterdam,","place":["The Netherlands"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Chen","sequence":"additional","affiliation":[{"name":"The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania , Philadelphia, PA 19104,","place":["United States"]},{"name":"The Graduate Group in Applied Mathematics and Computational Science, School of Arts and Sciences, University of Pennsylvania , Philadelphia, PA 19104,","place":["United States"]},{"name":"Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine , Philadelphia, PA 19104,","place":["United States"]},{"name":"Leonard Davis Institute of Health Economics , Philadelphia, PA 19104,","place":["United States"]},{"name":"Penn Medicine Center for Evidence-Based Practice (CEP) , Philadelphia, PA 19104,","place":["United States"]},{"name":"Penn Institute for Biomedical Informatics (IBI) , Philadelphia, PA 19104,","place":["United States"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2025,11,19]]},"reference":[{"key":"2026031216463666300_ocaf198-B1","first-page":"574","volume-title":"MEDINFO 2015: eHealth-enabled health","author":"Hripcsak","year":"2015"},{"key":"2026031216463666300_ocaf198-B2","doi-asserted-by":"crossref","first-page":"578","DOI":"10.1136\/amiajnl-2014-002747","article-title":"Launching PCORnet, a national patient-centered clinical research network","volume":"21","author":"Fleurence","year":"2014","journal-title":"J Am Med Inform Assoc"},{"key":"2026031216463666300_ocaf198-B3","doi-asserted-by":"crossref","first-page":"e0286297","DOI":"10.1371\/journal.pone.0286297","article-title":"Researching COVID to Enhance Recovery (RECOVER) adult study protocol: rationale, objectives, and design","volume":"18","author":"Horwitz","year":"2023","journal-title":"PLoS One."},{"key":"2026031216463666300_ocaf198-B4","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1093\/jamia\/ocaa196","article-title":"The National COVID Cohort Collaborative (N3C): rationale, design, infrastructure, and deployment","volume":"28","author":"Haendel","year":"2021","journal-title":"J Am Med Inform Assoc"},{"key":"2026031216463666300_ocaf198-B5","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1056\/NEJMsr1809937","article-title":"The \u201cAll of Us\u201d research program","volume":"381","author":"Investigators A of URP","year":"2019","journal-title":"N Engl J Med"},{"key":"2026031216463666300_ocaf198-B6","first-page":"239","author":"Wu","year":"2004"},{"key":"2026031216463666300_ocaf198-B7","doi-asserted-by":"crossref","first-page":"645","DOI":"10.1093\/aje\/kwt010","article-title":"Evaluating the impact of database heterogeneity on observational study results","volume":"178","author":"Madigan","year":"2013","journal-title":"Am J Epidemiol."},{"key":"2026031216463666300_ocaf198-B8","doi-asserted-by":"crossref","first-page":"289","DOI":"10.2307\/2531813","article-title":"Extended Mantel-Haenszel estimating procedure for multivariate logistic regression models","volume":"43","author":"Liang","year":"1987","journal-title":"Biometrics."},{"key":"2026031216463666300_ocaf198-B9","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1136\/amiajnl-2012-000862","article-title":"G rid Binary LO gistic RE gression (GLORE): building shared models without sharing data","volume":"19","author":"Wu","year":"2012","journal-title":"J Am Med Inform Assoc."},{"key":"2026031216463666300_ocaf198-B10","doi-asserted-by":"crossref","first-page":"1212","DOI":"10.1093\/jamia\/ocv083","article-title":"WebDISCO: a web service for distributed cox model learning without patient-level data sharing","volume":"22","author":"Lu","year":"2015","journal-title":"J Am Med Inform Assoc."},{"key":"2026031216463666300_ocaf198-B11","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1136\/amiajnl-2014-002751","article-title":"pSCANNER: patient-centered Scalable National Network for Effectiveness Research","volume":"21","author":"Ohno-Machado","year":"2014","journal-title":"J Am Med Inform Assoc"},{"key":"2026031216463666300_ocaf198-B12","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1146\/annurev-biodatasci-122220-115746","article-title":"Centralized and federated models for the analysis of clinical data","volume":"7","author":"Li","journal-title":"Annu Rev Biomed Data Sci"},{"key":"2026031216463666300_ocaf198-B13","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1142\/9789813279827_0004","volume-title":"BIOCOMPUTING 2019: Proceedings of the Pacific Symposium","author":"Duan","year":"2018"},{"key":"2026031216463666300_ocaf198-B14","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1142\/9789811215636_0061","volume-title":"Pacific Symposium on Biocomputing 2020","author":"Tong","year":"2019"},{"key":"2026031216463666300_ocaf198-B15","doi-asserted-by":"crossref","first-page":"19647","DOI":"10.1038\/s41598-021-99078-2","article-title":"An efficient and accurate distributed learning algorithm for modeling multi-site zero-inflated count outcomes","volume":"11","author":"Edmondson","year":"2021","journal-title":"Sci Rep"},{"key":"2026031216463666300_ocaf198-B16","doi-asserted-by":"crossref","first-page":"11073","DOI":"10.1038\/s41598-022-14029-9","article-title":"Multisite learning of high-dimensional heterogeneous data with applications to opioid use disorder study of 15,000 patients across 5 clinical sites","volume":"12","author":"Liu","year":"2022","journal-title":"Sci Rep."},{"key":"2026031216463666300_ocaf198-B17","doi-asserted-by":"crossref","first-page":"6627","DOI":"10.1038\/s41598-022-09069-0","article-title":"ODACH: a one-shot distributed algorithm for Cox model with heterogeneous multi-center data","volume":"12","author":"Luo","year":"2022","journal-title":"Sci Rep."},{"key":"2026031216463666300_ocaf198-B18","doi-asserted-by":"crossref","first-page":"104097","DOI":"10.1016\/j.jbi.2022.104097","article-title":"Distributed Quasi-Poisson regression algorithm for modeling multi-site count outcomes in distributed data networks","volume":"131","author":"Edmondson","year":"2022","journal-title":"J Biomed Inform."},{"key":"2026031216463666300_ocaf198-B19","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1038\/s41746-022-00615-8","article-title":"Distributed learning for heterogeneous clinical data with application to integrating COVID-19 data across 230 sites","volume":"5","author":"Tong","year":"2022","journal-title":"NPJ Digit Med."},{"key":"2026031216463666300_ocaf198-B20","doi-asserted-by":"crossref","first-page":"1366","DOI":"10.1093\/jamia\/ocac067","article-title":"dPQL: a lossless distributed algorithm for generalized linear mixed model with application to privacy-preserving hospital profiling","volume":"29","author":"Luo","year":"2022","journal-title":"J Am Med Inform Assoc."},{"key":"2026031216463666300_ocaf198-B21","doi-asserted-by":"crossref","first-page":"1028","DOI":"10.1093\/jamia\/ocaa044","article-title":"Learning from local to global: an efficient distributed algorithm for modeling time-to-event data","volume":"27","author":"Duan","year":"2020","journal-title":"J Am Med Inform Assoc."},{"key":"2026031216463666300_ocaf198-B22","doi-asserted-by":"crossref","first-page":"104595","DOI":"10.1016\/j.jbi.2024.104595","article-title":"One-shot distributed algorithms for addressing heterogeneity in competing risks data across clinical sites","volume":"150","author":"Zhang","year":"2024","journal-title":"J Biomed Inform."},{"key":"2026031216463666300_ocaf198-B23","doi-asserted-by":"crossref","first-page":"1102","DOI":"10.1093\/jamia\/ocae027","article-title":"Learning competing risks across multiple hospitals: one-shot distributed algorithms","volume":"31","author":"Zhang","year":"2024","journal-title":"J Am Med Inform Assoc."},{"key":"2026031216463666300_ocaf198-B24","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1146\/annurev-biodatasci-103123-094441","article-title":"Meta-analysis and federated learning over decentralized distributed research networks","volume":"8","author":"Lu","year":"2025","journal-title":"Annu Rev Biomed Data Sci"},{"key":"2026031216463666300_ocaf198-B25","doi-asserted-by":"crossref","first-page":"104476","DOI":"10.1016\/j.jbi.2023.104476","article-title":"Pad\u00e9 approximant meets federated learning: a nearly lossless, one-shot algorithm for evidence synthesis in distributed research networks with rare outcomes","volume":"145","author":"Wu","year":"2023","journal-title":"J Biomed Inform."},{"key":"2026031216463666300_ocaf198-B26","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1109\/TKDE.2006.196","article-title":"Regression cubes with lossless compression and aggregation","volume":"18","author":"Chen","year":"2006","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2026031216463666300_ocaf198-B27","doi-asserted-by":"crossref","first-page":"1678","DOI":"10.1038\/s41467-022-29160-4","article-title":"DLMM as a lossless one-shot algorithm for collaborative multi-site distributed linear mixed models","volume":"13","author":"Luo","year":"2022","journal-title":"Nat Commun."},{"key":"2026031216463666300_ocaf198-B28","author":"Penn Computing Inference Learning (PennCIL) lab"},{"key":"2026031216463666300_ocaf198-B29","author":"CMS Cell Size Suppression Policy"},{"key":"2026031216463666300_ocaf198-B30","author":"California Department of Health Care Services"},{"key":"2026031216463666300_ocaf198-B31","author":"Department of Health Agency"},{"key":"2026031216463666300_ocaf198-B32","author":"Utah Department of Health"},{"key":"2026031216463666300_ocaf198-B33","first-page":"439","article-title":"Quasi-likelihood functions, generalized linear models, and the Gauss\u2014Newton method","volume":"61","author":"Wedderburn","year":"1974","journal-title":"Biometrika."},{"key":"2026031216463666300_ocaf198-B34","doi-asserted-by":"crossref","first-page":"2766","DOI":"10.1890\/07-0043.1","article-title":"Quasi-Poisson vs negative binomial regression: how should we model overdispersed count data?","volume":"88","author":"Ver Hoef","year":"2007","journal-title":"Ecology."},{"key":"2026031216463666300_ocaf198-B35","doi-asserted-by":"crossref","first-page":"165","DOI":"10.7326\/M23-1754","article-title":"Real-world effectiveness of BNT162b2 against infection and severe diseases in children and adolescents","volume":"177","author":"Wu","year":"2024","journal-title":"Ann Intern Med"},{"key":"2026031216463666300_ocaf198-B36","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1016\/j.acap.2018.02.010","article-title":"Development and validation of the Pediatric Medical Complexity Algorithm (PMCA) version 3.0","volume":"18","author":"Simon","year":"2018","journal-title":"Acad Pediatr."},{"key":"2026031216463666300_ocaf198-B37","doi-asserted-by":"crossref","first-page":"3445","DOI":"10.1038\/s41467-025-56284-0","article-title":"Cardiovascular post-acute sequelae of SARS-CoV-2 in children and adolescents: cohort study using electronic health records","volume":"16","author":"Zhang","year":"2025","journal-title":"Nat Commun."},{"key":"2026031216463666300_ocaf198-B38","doi-asserted-by":"crossref","first-page":"e314","DOI":"10.1093\/ije\/dyac026","article-title":"Data resource profile: the integrated primary care information (IPCI) database, The Netherlands","volume":"51","author":"de Ridder","year":"2022","journal-title":"Int J Epidemiol."},{"key":"2026031216463666300_ocaf198-B39","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1007\/s11154-021-09630-8","article-title":"Diabetes is most important cause for mortality in COVID-19 hospitalized patients: systematic review and meta-analysis","volume":"22","author":"Corona","year":"2021","journal-title":"Rev Endocr Metab Disord."},{"key":"2026031216463666300_ocaf198-B40","doi-asserted-by":"crossref","first-page":"745","DOI":"10.1016\/j.numecd.2020.12.009","article-title":"Hypertension is a clinically important risk factor for critical illness and mortality in COVID-19: a meta-analysis","volume":"31","author":"Du","year":"2021","journal-title":"Nutr Metab Cardiovasc Dis."},{"key":"2026031216463666300_ocaf198-B41","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1016\/j.jamda.2020.05.045","article-title":"The effect of age on mortality in patients with COVID-19: a meta-analysis with 611,583 subjects","volume":"21","author":"Bonanad","year":"2020","journal-title":"J Am Med Dir Assoc."},{"key":"2026031216463666300_ocaf198-B42","doi-asserted-by":"crossref","first-page":"e0254066","DOI":"10.1371\/journal.pone.0254066","article-title":"Male gender is a predictor of higher mortality in hospitalized adults with COVID-19","volume":"16","author":"Nguyen","year":"2021","journal-title":"PLoS One."},{"key":"2026031216463666300_ocaf198-B43","doi-asserted-by":"crossref","first-page":"1695","DOI":"10.1080\/01621459.2024.2443246","article-title":"Robust inference for federated meta-learning","volume":"120","author":"Guo","year":"2025","journal-title":"J Am Stat Assoc."}],"container-title":["Journal of the American Medical Informatics Association"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/jamia\/advance-article-pdf\/doi\/10.1093\/jamia\/ocaf198\/65394863\/ocaf198.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jamia\/article-pdf\/33\/3\/700\/65394863\/ocaf198.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jamia\/article-pdf\/33\/3\/700\/65394863\/ocaf198.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T20:46:45Z","timestamp":1773348405000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jamia\/article\/33\/3\/700\/8328038"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,19]]},"references-count":43,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025,11,19]]},"published-print":{"date-parts":[[2026,3,1]]}},"URL":"https:\/\/doi.org\/10.1093\/jamia\/ocaf198","relation":{},"ISSN":["1067-5027","1527-974X"],"issn-type":[{"value":"1067-5027","type":"print"},{"value":"1527-974X","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026,3]]},"published":{"date-parts":[[2025,11,19]]}}}