Using machine learning models based on cardiac magnetic resonance parameters to predict the prognostic in children with myocarditis.

Journal: BMC pediatrics
Published Date:

Abstract

OBJECTIVE: To develop machine learning (ML) models incorporating explanatory cardiac magnetic resonance (CMR) parameters for predicting the prognosis of myocarditis in pediatric patients.

Authors

  • Dongliang Hu
    Department of Radiology, The Second Affiliated Hospital of Soochow University, San Xiang Road No. 1055, Suzhou, 215004, Jiangsu, China.
  • Manman Cui
    Department of Radiology, The Second Affiliated Hospital of Soochow University, San Xiang Road No. 1055, Suzhou, 215004, Jiangsu, China.
  • Xueke Zhang
    Department of Radiology, The Second Affiliated Hospital of Soochow University, San Xiang Road No. 1055, Suzhou, 215004, Jiangsu, China.
  • Yuanyuan Wu
    Department of Mathematics, Southeast University, Nanjing 210096, China; College of Electric and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China.
  • Yan Liu
    Department of Clinical Microbiology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200072, People's Republic of China.
  • Duchang Zhai
    Department of Radiology, The Second Affiliated Hospital of Soochow University, San Xiang Road No. 1055, Suzhou, 215004, Jiangsu, China.
  • Wanliang Guo
    Department of Radiology, Children's Hospital of Soochow University, Suzhou, 215025, China. gwlsuzhou@163.com.
  • Shenghong Ju
  • Guohua Fan
    Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.
  • Wu Cai
    Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China.