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 …

Objectives We aimed to build a machine learning predictive model to predict the risk of
prolonged mechanical ventilation (PMV) for patients with Traumatic Brain Injury (TBI) …

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 …

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 …

Purpose With the in-depth application of machine learning (ML) in clinical practice, it has
been used to predict the mortality risk in patients with traumatic brain injuries (TBI). However …

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

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

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

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 …

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