Introduction Few studies on early functional outcomes following acute care after traumatic
brain injury (TBI) are available. The aim of this study was to develop and validate a …

Background Traumatic brain injury (TBI), which occurs commonly worldwide, is among the
more costly of health and socioeconomic problems. Accurate prediction of favorable …

Background With this study we aimed to design validated outcome prediction models in
moderate and severe traumatic brain injury (TBI) using demographic, clinical, and …

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 …

The difficulty of accurately identifying patients who would benefit from promising treatments
makes it challenging to prove the efficacy of novel treatments for traumatic brain injury (TBI) …

OBJECTIVE An estimated 1.5 million people die every year worldwide from traumatic brain
injury (TBI). Physicians are relatively poor at predicting long-term outcomes early in patients …

Introduction Traumatic brain injury (TBI) is a heterogeneous condition with a broad spectrum
of injury severity, pathophysiological processes and variable outcomes. For moderate-to …

Aim Controversy remains high over the superiority of advanced machine learning (ML)
algorithms to conventional logistic regression (LR) in the prediction of prognosis after …

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 …

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