Background Machine learning (ML) has been used to predict the outcomes of traumatic
brain injury. However, few studies have reported the use of ML models to predict early …

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 …

Background There is paucity in the literature to predict the occurrence of Ventilator
Associated Pneumonia (VAP) in patients with Traumatic Brain Injury (TBI). We aimed to build …

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 …

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 …

BACKGROUND: Machine learning (ML) holds promise as a tool to guide clinical decision
making by predicting in-hospital mortality for patients with traumatic brain injury (TBI) …

Traumatic brain injury (TBI) remains a critical public health challenge. Although studies have
found several prognostic factors for TBI, a useful early predictive tool for mortality has yet to …

Background Interest in models for calculating the risk of death in traumatic patients admitted
to ICUs remains high. These models use variables derived from the deviation of …

Our aim was to create simple and largely scalable machine learning-based algorithms that
could predict mortality in a real-time fashion during intensive care after traumatic brain injury …

Background: In a time when the incidence of severe traumatic brain injury (TBI) is increasing
in low-to middle-income countries (LMICs), it is important to understand the behavior of …