Expert-level differentiation of incomplete Kawasaki disease and pneumonia from echocardiography via multiple large receptive attention mechanisms.

Journal: Computers in biology and medicine
Published Date: Jun 19, 2025

Abstract

BACKGROUND: Incomplete Kawasaki disease (KD) is challenging to diagnose due to its lack of classic clinical features, yet it has a higher incidence of coronary artery lesions, making early detection crucial. Echocardiography plays a vital role in identifying these lesions, but differentiating incomplete KD from other febrile illnesses, such as COVID-19, is difficult. Algorithms capable of achieving expert-level performance are needed to aid diagnosis, particularly in the absence of pediatric cardiologists.

Authors

  • Haeyun Lee
  • Kyungsu Lee
    Information and Communication Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu 42988, Korea.
  • Moon Hwan Lee
    Information and Communication Engineering, Daegu Gyeongbuk Institute of Science and Technology, Daegu 42988, Korea.
  • Sewoong Kim
  • Yongsoon Eun
    Department of Electrical Engineering and Computer Science; The Interdisciplinary Studies of Artificial Intelligence.
  • Lucy Youngmin Eun
    Division of Pediatric Cardiology, Department of Pediatrics, Yonsei University College of Medicine, Seoul 03722, South Korea. Electronic address: lucyeun@yuhs.ac.
  • Jae Youn Hwang

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