Atrial fibrillation classification based on convolutional neural networks.

Journal: BMC medical informatics and decision making
Published Date:

Abstract

BACKGROUND: The global age-adjusted mortality rate related to atrial fibrillation (AF) registered a rapid growth in the last four decades, i.e., from 0.8 to 1.6 and 0.9 to 1.7 per 100,000 for men and women during 1990-2010, respectively. In this context, this study uses convolutional neural networks for classifying (diagnosing) AF, employing electrocardiogram data in a general hospital.

Authors

  • Kwang-Sig Lee
    AI Center, Korea University College of Medicine, Seoul, South Korea.
  • Sunghoon Jung
    HUINNO Co., Ltd., Seoul, South Korea.
  • Yeongjoon Gil
    HUINNO Co., Ltd., Seoul, South Korea.
  • Ho Sung Son
    Department of Thoracic and Cardiovascular Surgery, Korea University College of Medicine, 73 Inchon-ro, Seongbook-gu, Seoul, 02841, South Korea. hssonmd@korea.ac.kr.