Machine Learning-Based Explainable Automated Nonlinear Computation Scoring System for Health Score and an Application for Prediction of Perioperative Stroke: Retrospective Study.

Journal: Journal of medical Internet research
PMID: 40106818

Abstract

BACKGROUND: Machine learning (ML) has the potential to enhance performance by capturing nonlinear interactions. However, ML-based models have some limitations in terms of interpretability.

Authors

  • Mi-Young Oh
    Department of Neurology, Sejong General Hospital, Sejong General Hospital, Bucheon-si, Republic of Korea.
  • Hee-Soo Kim
    Department of Anesthesiology and Pain Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea. dami0605@snu.ac.kr.
  • Young Mi Jung
    Department of Obstetrics and Gynecology, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea.
  • Hyung-Chul Lee
    From the Department of Anesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea.
  • Seung-Bo Lee
    Department of Brain and Cognitive Engineering, Korea University.
  • Seung Mi Lee
    Department of Obstetrics and Gynecology, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, South Korea.

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