Artificial intelligence-enabled electrocardiography from scientific research to clinical application.
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| Title: | Artificial intelligence-enabled electrocardiography from scientific research to clinical application. |
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| Authors: | Lin CS; Division of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC.; Medical Technology Education Center, School of Medicine, College of Medicine, National Defense Medical University, Taipei, Taiwan, ROC.; Military Digital Medical Center, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC., Liu WT; Division of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC., Chen YH; Department of Neurological Surgery, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC., Lin SH; Division of Nephrology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC., Lin C; Medical Technology Education Center, School of Medicine, College of Medicine, National Defense Medical University, Taipei, Taiwan, ROC. xup6fup@mail.ndmctsgh.edu.tw.; Military Digital Medical Center, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC. xup6fup@mail.ndmctsgh.edu.tw. |
| Source: | EMBO molecular medicine [EMBO Mol Med] 2026 Jan; Vol. 18 (1), pp. 22-40. Date of Electronic Publication: 2025 Dec 01. |
| Publication Type: | Journal Article; Review |
| Journal Info: | Publisher: EMBO Press Country of Publication: Germany NLM ID: 101487380 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1757-4684 (Electronic) Linking ISSN: 17574676 NLM ISO Abbreviation: EMBO Mol Med Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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