Predicting Inpatient Length of Stay After Brain Tumor Surgery: Developing Machine Learning Ensembles to Improve Predictive Performance.

Journal: Neurosurgery
Published Date: Sep 1, 2019

Abstract

BACKGROUND: Current outcomes prediction tools are largely based on and limited by regression methods. Utilization of machine learning (ML) methods that can handle multiple diverse inputs could strengthen predictive abilities and improve patient outcomes. Inpatient length of stay (LOS) is one such outcome that serves as a surrogate for patient disease severity and resource utilization.

Authors

  • Whitney E Muhlestein
    Department of Neurosurgery, Vanderbilt University Medical Center, Vanderbilt University, Nashville, Tennessee, United States.
  • Dallin S Akagi
    DataRobot, Inc., Boston, Massachusetts, United States.
  • Jason M Davies
    Philip R. Lee Institute for Health Policy Studies, School of Medicine, University of California, San Francisco.
  • Lola B Chambless
    Department of Neurosurgery, Vanderbilt University Medical Center, Vanderbilt University, Nashville, Tennessee, United States.

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