Machine Learning techniques for predicting mortality in Traumatic Brain Injury: a systematic review of the literature. Silva-Sousa, A. A., Queiroz, R. A. B., Miranda, A. S., Instituto de Ciências Biológicas, UFMG, Belo Horizonte/MG

Traumatic brain injury (TBI) has been recognized as one of the main causes of morbidity and mortality worldwide, being considered a silent epidemic. A variety of causes of TBI are considered, such as falls, car accidents, robberies and assaults. Despite intense investments, there is not still an approved treatment to mitigate the damage caused by secondary TBI injuries, and prevention is currently the best treatment. With technological advances, machine learning (ML) techniques have been used in the health field to predict outcomes and aid in therapeutic decision-making, for example, mortality risk in TBI victims. However, to the same extent that there is a significant development of ML techniques for this purpose, there is no consensus on which strategies have the best performance in predicting mortality.