COLA-GLM: collaborative one-shot and lossless algorithms of generalized linear models for decentralized observational healthcare data.

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Title: COLA-GLM: collaborative one-shot and lossless algorithms of generalized linear models for decentralized observational healthcare data.
Authors: Wu Q; Department of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, PA, USA.; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.; The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA., Reps JM; Observational Health Data Sciences and Informatics, New York, NY, USA.; Janssen Research & Development, Titusville, NJ, USA.; Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands., Li L; The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.; The Graduate Group in Applied Mathematics and Computational Science, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA., Zhang B; The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.; The Graduate Group in Applied Mathematics and Computational Science, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA., Lu Y; The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.; The Graduate Group in Applied Mathematics and Computational Science, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA., Tong J; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.; The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA.; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA., Zhang D; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.; The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA., Lumley T; Department of Statistics, Faculty of Science, University of Auckland, Auckland, New Zealand., Brand MT; Real World Solutions, IQVIA, Durham, NC, USA., Van Zandt M; Observational Health Data Sciences and Informatics, New York, NY, USA.; Real World Solutions, IQVIA, Durham, NC, USA., Falconer T; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA., He X; Department of Biostatistics and Health Data Science, Indiana University, Indianapolis, IN, USA.; Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA., Huang Y; Department of Biostatistics and Health Data Science, Indiana University, Indianapolis, IN, USA.; Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA., Li H; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA., Yan C; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA., Tang G; Department of Electrical and Software Engineering, University of Calgary, Calgary, AB, Canada., Williams AE; Clinical and Translational Science Institute, Tufts Medical Center, Boston, MA, USA.; Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA., Wang F; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA., Bian J; Department of Biostatistics and Health Data Science, Indiana University, Indianapolis, IN, USA.; Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, USA., Malin B; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.; Department of Computer Science, Vanderbilt University, Nashville, TN, USA., Hripcsak G; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA., Schuemie MJ; Observational Health Data Sciences and Informatics, New York, NY, USA.; Janssen Research & Development, Titusville, NJ, USA.; Department of Biostatistics, University of California, Los Angeles, CA, USA., Lu Y; Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA., Drew S; Department of Electrical and Software Engineering, University of Calgary, Calgary, AB, Canada., Zhou J; School of Information, University of Michigan, Ann Arbor, MI, USA., Asch DA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA.; Division of General Internal Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA., Chen Y; Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA. ychen123@upenn.edu.; The Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, PA, USA. ychen123@upenn.edu.; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA, USA. ychen123@upenn.edu.; Penn Medicine Center for Evidence-based Practice (CEP), Philadelphia, PA, USA. ychen123@upenn.edu.; Penn Institute for Biomedical Informatics (IBI), Philadelphia, PA, USA. ychen123@upenn.edu.
Source: NPJ digital medicine [NPJ Digit Med] 2025 Jul 15; Vol. 8 (1), pp. 442. Date of Electronic Publication: 2025 Jul 15.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101731738 Publication Model: Electronic Cited Medium: Internet ISSN: 2398-6352 (Electronic) Linking ISSN: 23986352 NLM ISO Abbreviation: NPJ Digit Med Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2398-6352
DOI:10.1038/s41746-025-01781-1