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 …

Background The purpose of this study was to build a model of machine learning (ML) for the
prediction of mortality in patients with isolated moderate and severe traumatic brain injury …

Prognostic prediction of traumatic brain injury (TBI) in patients is crucial in clinical decision
and health care policy making. This study aimed to develop and validate prediction models …

Recently, successful predictions using machine learning (ML) algorithms have been
reported in various fields. However, in traumatic brain injury (TBI) cohorts, few studies have …

Background The study aimed to introduce a machine learning model that predicts in-hospital
mortality in patients on mechanical ventilation (MV) following moderate to severe traumatic …

Predicting treatment outcomes in traumatic brain injury (TBI) patients is challenging
worldwide. The present study aimed to achieve the most accurate machine learning (ML) …

Purpose To compare twenty-two machine learning (ML) models against logistic regression
on survival prediction in severe traumatic brain injury (STBI) patients in a single center study …

Background: Traumatic brain injury (TBI) is a leading cause of death and disability
worldwide. The use of machine learning (ML) has emerged as a key advancement in TBI …

Traumatic brain injury (TBI) can lead to severe adverse clinical outcomes, including death
and disability. Early detection of in-hospital mortality in high-risk populations may enable …

One of the main challenges in traumatic brain injury (TBI) patients is to achieve an early and
definite prognosis. Despite the recent development of algorithms based on artificial …