Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47803, first published .
Optimization of Using Multiple Machine Learning Approaches in Atrial Fibrillation Detection Based on a Large-Scale Data Set of 12-Lead Electrocardiograms: Cross-Sectional Study

Optimization of Using Multiple Machine Learning Approaches in Atrial Fibrillation Detection Based on a Large-Scale Data Set of 12-Lead Electrocardiograms: Cross-Sectional Study

Optimization of Using Multiple Machine Learning Approaches in Atrial Fibrillation Detection Based on a Large-Scale Data Set of 12-Lead Electrocardiograms: Cross-Sectional Study

Authors of this article:

Beau Bo-Sheng Chuang1 Author Orcid Image ;   Albert C Yang1, 2, 3 Author Orcid Image

Journals

  1. Hussain S, Ahmad S, Wasid M. Artificial intelligence-driven intelligent learning models for identification and prediction of cardioneurological disorders: A comprehensive study. Computers in Biology and Medicine 2025;184:109342 View
  2. Chirieleison C, Cezar M, Almeida L, Porto C, Santos J, Silva Y, Brêda M, Araujo D. Tecnologias vestíveis no monitoramento de cardiopatias: uma revisão de literatura. Cuadernos de Educación y Desarrollo 2024;16(12 Edição Especial):e6483 View