Artificial Intelligence-Enabled Electrocardiography Identifies Osteoporosis and has Prognostic Value.

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Bibliographic Details
Title: Artificial Intelligence-Enabled Electrocardiography Identifies Osteoporosis and has Prognostic Value.
Authors: Hsing SC; Division of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical University, Taipei, R.O.C, Taiwan., Tsai DJ; Medical Technology Education Center, School of Medicine, National Defense Medical University, Taipei, R.O.C, Taiwan.; Artificial Intelligence of Things Center, Tri-Service General Hospital, National Defense Medical University, Taipei, R.O.C, Taiwan., Lin C; Medical Technology Education Center, School of Medicine, National Defense Medical University, Taipei, R.O.C, Taiwan.; Artificial Intelligence of Things Center, Tri-Service General Hospital, National Defense Medical University, Taipei, R.O.C, Taiwan.; School of Public Health, National Defense Medical University, Taipei, R.O.C, Taiwan., Lin CS; Division of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical University, Taipei, R.O.C, Taiwan., Lee CC; Tri-Service General Hospital, Medical Informatics Office, National Defense Medical University, Taipei, R.O.C, Taiwan.; Division of Colorectal Surgery, Department of Surgery, Tri-Service General Hospital, National Defense Medical University, Taipei, R.O.C, Taiwan., Wang CH; Department of Otolaryngology-Head and Neck Surgery, Tri-Service General Hospital, National Defense Medical University, Taipei, R.O.C, Taiwan.; Graduate Institute of Medical Sciences, National Defense Medical University, Taipei, R.O.C, Taiwan., Fang WH; Artificial Intelligence of Things Center, Tri-Service General Hospital, National Defense Medical University, Taipei, R.O.C, Taiwan. rumaf.fang@gmail.com.; Department of Family and Community Medicine, Tri-Service General Hospital, National Defense Medical University, R.O.C. No 161, Min-Chun E. Rd., Sec. 6, Taipei, Neihu, 11490, Taipei, Taiwan. rumaf.fang@gmail.com.
Source: Journal of medical systems [J Med Syst] 2025 Dec 26; Vol. 49 (1), pp. 191. Date of Electronic Publication: 2025 Dec 26.
Publication Type: Journal Article; Multicenter Study; Validation Study
Journal Info: Publisher: Kluwer Academic/Plenum Publishers Country of Publication: United States NLM ID: 7806056 Publication Model: Electronic Cited Medium: Internet ISSN: 1573-689X (Electronic) Linking ISSN: 01485598 NLM ISO Abbreviation: J Med Syst Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1573-689X
DOI:10.1007/s10916-025-02333-6