Machine-learning approach to atrial fibrillation prediction among individuals without prior cardiovascular diseases.

Journal: Open heart
Published Date: Aug 22, 2025

Abstract

BACKGROUND: There is a lack of atrial fibrillation (AF) prediction models tailored for individuals without prior cardiovascular diseases (CVDs) to facilitate early intervention. This study aimed to develop and validate an AF prediction model using machine-learning methods based on routine biomarkers in middle-aged individuals without overt CVD.

Authors

  • Mozhu Ding
    Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden mozhu.ding@ki.se.
  • Shunsuke Murata
    Department of Preventive Medicine and Epidemiology, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan.
  • Javier Louro
    Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
  • Niklas Hammar
    Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
  • Karin Modig
    Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.

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