Photoplethysmography-Based Machine Learning Approaches for Atrial Fibrillation Prediction: A Report From the Huawei Heart Study.

Journal: JACC. Asia
Published Date: Dec 21, 2021

Abstract

BACKGROUND: Current wearable devices enable the detection of atrial fibrillation (AF), but a machine learning (ML)-based approach may facilitate accurate prediction of AF onset.

Authors

  • Yutao Guo
    Department of Pulmonary Vessel and Thrombotic Disease, Sixth Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Hao Wang
    Department of Cardiology, Second Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Hui Zhang
    Department of Pulmonary Vessel and Thrombotic Disease, Sixth Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Tong Liu
    Intensive Care Medical Center, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, People's Republic of China.
  • Luping Li
    Huawei Technologies Co, Shenzhen, China.
  • Lingjie Liu
    Huawei Technologies Co, Shenzhen, China.
  • Maolin Chen
    Huawei Technologies Co, Shenzhen, China.
  • Yundai Chen
    Department of Pulmonary Vessel and Thrombotic Disease, Sixth Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Gregory Y H Lip
    Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital, L69 3BX Liverpool, UK.

Keywords

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