The effect of selection bias on the performance of a deep learning-based intraoperative hypotension prediction model using real-world samples from a publicly available database.

Journal: British journal of anaesthesia
Published Date: May 22, 2025

Abstract

BACKGROUND: There are models to predict intraoperative hypotension from arterial pressure waveforms. Selection bias in datasets used for model development and validation could impact model performance. We aimed to evaluate how selection bias affects the predictive performance of a deep learning (DL)-based model and a model using only mean arterial pressure (MAP) as input (MAP-only model).

Authors

  • Hyun-Lim Yang
    Department of Information and Communication Engineering, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Daegu, Republic of Korea.
  • Leo Anthony Celi
    Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Hyeonhoon Lee
    Department of Clinical Korean Medicine, Graduate School, Kyung Hee University, Seoul, Republic of Korea.
  • Seong-A Park
    Department of Anesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
  • Sangjin Lee
    Department of Cardiovascular Surgery, Spectrum Health Grand Rapids, Grand Rapids, MI, USA.
  • Chul-Woo Jung
  • Hyung-Chul Lee
    From the Department of Anesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea.

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