Evaluation of Machine Learning Techniques to Predict the Likelihood of Mental Health Conditions Following a First mTBI.

Journal: Frontiers in neurology
Published Date: Feb 2, 2022

Abstract

OBJECTIVE: Limited research has evaluated the utility of machine learning models and longitudinal data from electronic health records (EHR) to forecast mental health outcomes following a traumatic brain injury (TBI). The objective of this study is to assess various data science and machine learning techniques and determine their efficacy in forecasting mental health (MH) conditions among active duty Service Members (SMs) following a first diagnosis of mild traumatic brain injury (mTBI).

Authors

  • Filip Dabek
    National Intrepid Center of Excellence (NICoE), Bethesda, MD, United States.
  • Peter Hoover
    National Intrepid Center of Excellence (NICoE), Bethesda, MD, United States.
  • Kendra Jorgensen-Wagers
    Landstuhl Regional Medical Center, Landstuhl, Germany.
  • Tim Wu
    National Intrepid Center of Excellence (NICoE), Bethesda, MD, United States.
  • Jesus J Caban
    National Intrepid Center of Excellence (NICoE), Bethesda, MD, United States.

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