Unsupervised characterization of 100,272 EHR patients identifies high-risk groups and comorbidities linked to premature aging.

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Title: Unsupervised characterization of 100,272 EHR patients identifies high-risk groups and comorbidities linked to premature aging.
Authors: Xian S; Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA. suxian06@gmail.com., Smoller JW; Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.; Department of Psychiatry, Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA., Luo Y; Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA., Walunas TL; Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA., Liu C; Department of Pediatrics, Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA., Khan A; Department of Medicine, Columbia University Irving Medical Center, Columbia University, New York, NY, USA., Weng C; Department of Biomedical Informatics, Columbia University, New York, NY, USA., Kullo IJ; Department of Cardiovascular Medicine and the Gonda Vascular Center, Mayo Clinic Rochester Minnesota, Rochester, MN, USA., Wei WQ; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA., Jarvik GP; Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA, USA.; Department of Genome Sciences, University of Washington, Seattle, WA, USA., Crosslin DR; Department of Medicine, Division of Biomedical Informatics and Genomics, Tulane University, New Orleans, LA, USA.
Source: NPJ digital medicine [NPJ Digit Med] 2026 Jun 23. Date of Electronic Publication: 2026 Jun 23.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101731738 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2398-6352 (Electronic) Linking ISSN: 23986352 NLM ISO Abbreviation: NPJ Digit Med
Database: MEDLINE Ultimate
Description
ISSN:2398-6352
DOI:10.1038/s41746-026-02913-x