SurgeryLSTM: a time-aware neural model for accurate and explainable length of stay prediction after spine surgery.

Journal: JAMIA open
Published Date: Jul 25, 2025

Abstract

OBJECTIVE: To develop and evaluate machine learning (ML) models for predicting length of stay (LOS) in elective spine surgery, with a focus on the benefits of temporal modeling and model interpretability.

Authors

  • Ha Na Cho
    Division of Cardiology, Department of Information Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympicro 43gil, 05505, Seoul, Songpagu, Korea.
  • Sairam Sutari
    University of California Irvine, Irvine, CA 92697, United States.
  • Alexander Lopez
    Department of Neurosurgery, University of California, Irvine, Orange, CA 92868, United States.
  • Hansen Bow
    Department of Neurosurgery, University of California, Irvine, Orange, CA 92868, United States.
  • Kai Zheng
    University of California, Irvine, Irvine, CA, USA.

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