Prediction of in-hospital mortality in patients with post traumatic brain injury using National Trauma Registry and Machine Learning Approach.

Journal: Scandinavian journal of trauma, resuscitation and emergency medicine
Published Date: May 27, 2020

Abstract

BACKGROUND: The use of machine learning techniques to predict diseases outcomes has grown significantly in the last decade. Several studies prove that the machine learning predictive techniques outperform the classical multivariate techniques. We aimed to build a machine learning predictive model to predict the in-hospital mortality for patients who sustained Traumatic Brain Injury (TBI).

Authors

  • Ahmad Abujaber
    Assistant Executive Director of Nursing, Hamad medical corporation, Doha, Qatar.
  • Adam Fadlalla
    Management Information Systems, Business, and Economics faculty at Qatar University, Doha, Qatar.
  • Diala Gammoh
    Industrial Engineering, University of Central Florida, Orlando, Florida, United States of America.
  • Husham Abdelrahman
    Department of Surgery, Trauma Surgery, Hamad Medical Corporation, Doha, Qatar.
  • Monira Mollazehi
    Department of Surgery, Trauma Surgery, Hamad Medical Corporation, Doha, Qatar.
  • Ayman El-Menyar
    Department of Surgery, Trauma Surgery, Clinical Research, Hamad Medical Corporation, Doha, Qatar.

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