Utilizing Machine Learning Methods for Preoperative Prediction of Postsurgical Mortality and Intensive Care Unit Admission.

Journal: Annals of surgery
Published Date:

Abstract

OBJECTIVE: To compare the performance of machine learning models against the traditionally derived Combined Assessment of Risk Encountered in Surgery (CARES) model and the American Society of Anaesthesiologists-Physical Status (ASA-PS) in the prediction of 30-day postsurgical mortality and need for intensive care unit (ICU) stay >24 hours.

Authors

  • Calvin J Chiew
    Health Services Research Unit, Division of Medicine, Singapore General Hospital.
  • Nan Liu
    Duke-NUS Medical School Centre for Quantitative Medicine Singapore Singapore.
  • Ting Hway Wong
    Health Services Research Unit, Division of Medicine, Singapore General Hospital.
  • Yilin E Sim
  • Hairil R Abdullah