This paper is in the following e-collection/theme issue:

Clinical Communication, Electronic Consultation and Telehealth (590) Telehealth and Telemonitoring (1671) Decision Support for Health Professionals (1185)

Published on in Vol 3, No 2 (2015): April-June

A Telesurveillance System With Automatic Electrocardiogram Interpretation Based on Support Vector Machine and Rule-Based Processing

A Telesurveillance System With Automatic Electrocardiogram Interpretation Based on Support Vector Machine and Rule-Based Processing

A Telesurveillance System With Automatic Electrocardiogram Interpretation Based on Support Vector Machine and Rule-Based Processing

Authors of this article:

Te-Wei Ho1 Author Orcid Image ;   Chen-Wei Huang2 Author Orcid Image ;   Ching-Miao Lin3 Author Orcid Image ;   Feipei Lai1 Author Orcid Image ;   Jian-Jiun Ding2 Author Orcid Image ;   Yi-Lwun Ho4 Author Orcid Image ;   Chi-Sheng Hung4 Author Orcid Image
Article Authors Cited by (11) Tweetations (3) Metrics

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  3. Jeon E, Oh K, Kwon S, Son H, Yun Y, Jung E, Kim M. A Lightweight Deep Learning Model for Fast Electrocardiographic Beats Classification With a Wearable Cardiac Monitor: Development and Validation Study. JMIR Medical Informatics 2020;8(3):e17037 View
  4. Zarinabad N, Meeus E, Manias K, Foster K, Peet A. Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis. JMIR Medical Informatics 2018;6(2):e30 View
  5. Chen Y, Hung C, Huang C, Lee J, Yu J, Ho Y. The Impact of Synchronous Telehealth Services With a Digital Platform on Day-by-Day Home Blood Pressure Variability in Patients with Cardiovascular Diseases: Retrospective Cohort Study. Journal of Medical Internet Research 2022;24(1):e22957 View
  6. Yang L, Lee J, Tsai C, Chen Y, Huang C, Wu H, Su C, Lee C, Hung C, Ho Y. Effect of Telehealth Services on Mitral and Tricuspid Regurgitation Progression: Retrospective Study. Journal of Medical Internet Research 2023;25:e47947 View