Explainable deep learning algorithm for distinguishing IVIG-Resistant Kawasaki disease in Shandong peninsula, China.

Journal: BMC pediatrics
Published Date: Aug 28, 2025

Abstract

BACKGROUND: Intravenous immunoglobulin (IVIG) resistance of Kawasaki disease (KD) patients have a heightened risk of coronary artery lesions. We aimed to explore the predictive factors of IVIG resistance of KD from Shandong Peninsula in China, and established a explainable prediction model based on deep learning.

Authors

  • Gang Luo
    Department of Biomedical Informatics and Medical Education, University of Washington UW Medicine South Lake Union, 850 Republican Street, Building C, Box 358047 Seattle, WA 98195, USA, luogang@uw.edu.
  • Huashu Liu
    Department of Pediatrics, Qingdao Central Hospital, University of Health and Rehabilitation Sciences (Qingdao Central Hospital), Qingdao, 266042, China.
  • Zhixin Li
    School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213000, China.
  • Zhixian Ji
    Heart Center, Women and Children's Hospital, Qingdao University, 6 Tongfu Road, Qingdao, 266034, China.
  • Sibao Wang
    Heart Center, Women and Children's Hospital, Qingdao University, 6 Tongfu Road, Qingdao, 266034, China.
  • Silin Pan
    Heart Center, Women and Children's Hospital, Qingdao University, 6 Tongfu Road, Qingdao, 266034, China. silinpan@126.com.

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