Continuous real-time prediction of surgical case duration using a modular artificial neural network.

Journal: British journal of anaesthesia
PMID: 35090725

Abstract

BACKGROUND: Real-time prediction of surgical duration can inform perioperative decisions and reduce surgical costs. We developed a machine learning approach that continuously incorporates preoperative and intraoperative information for forecasting surgical duration.

Authors

  • York Jiao
    Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri, USA.
  • Bing Xue
  • Chenyang Lu
    Department of Computer Science and Engineering, Washington University, St. Louis, MO.
  • Michael S Avidan
    Department of Anesthesiology, Washington University in St Louis, St Louis, MO, 63110, USA.
  • Thomas Kannampallil
    Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri, USA.

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