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

Journals

  1. Nguyen T, Qin X, Dinh A, Bui F. Low Resource Complexity R-peak Detection Based on Triangle Template Matching and Moving Average Filter. Sensors 2019;19(18):3997 View
  2. Chen Y, Hung C, Huang C, Hung Y, Hwang J, Ho Y. Atrial Fibrillation Screening in Nonmetropolitan Areas Using a Telehealth Surveillance System With an Embedded Cloud-Computing Algorithm: Prospective Pilot Study. JMIR mHealth and uHealth 2017;5(9):e135 View
  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