Development of a machine learning-based prediction model for serious bacterial infections in febrile young infants.

Journal: BMJ paediatrics open
Published Date:

Abstract

BACKGROUND: To develop and validate machine learning (ML)-based models to predict serious bacterial infections (SBIs) in febrile infants aged ≤90 days.

Authors

  • Jun Sung Park
    Department of Pediatrics, Division of Pediatric Emergency Medicine, Asan Medical Center.
  • Reenar Yoo
    Department of Convergence Medicine, Asan Medical Center, Asan Institutes for Life Sciences.
  • Soo-Young Lim
    Pediatric Emergency Department, Asan Medical Center Children's Hospital, Songpa-gu, 서울특별시, Korea (the Republic of).
  • Dahyun Kim
    School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea.
  • Min Kyo Chun
    Department of Pediatrics, Division of Pediatric Emergency Medicine, Asan Medical Center.
  • Jeeho Han
    Department of Pediatrics, Division of Pediatric Emergency Medicine, Asan Medical Center.
  • Jeong-Yong Lee
    Department of Pediatrics, Division of Pediatric Emergency Medicine, Asan Medical Center.
  • Seung Jun Choi
    3Department of Food Science and Technology, Seoul National University of Science and Technology, Seoul, 01811 Korea.
  • Seak Hee Oh
    Department of Pediatrics, Asan Medical Center Children's Hospital, Seoul, Korea (the Republic of) seakhee.oh@amc.seoul.kr.
  • Jong Seung Lee
    Department of Emergency Medicine, Asan Medical Center, College of Medicine, University of Ulsan, Seoul, Republic of Korea.
  • Jina Lee
    Microbiology and Functionality Research Group, World Institute of Kimchi, Gwangju 61755, Republic of Korea.