Purpose A reliable tool for outcome prognostication in severe traumatic brain injury (TBI)
would improve intensive care unit (ICU) decision-making process by providing objective …

Background Existing methods to predict recovery after severe traumatic brain injury lack
accuracy. The aim of this study is to determine the prognostic value of quantitative diffusion …

Background Prognostication in the early stage of traumatic coma is a common challenge in
the neuro-intensive care unit. We report the unexpected recovery of functional milestones …

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

Objective: The objective of the study is to test whether multimodal magnetic resonance
imaging can provide a reliable outcome prediction of the clinical status, focusing on …

Background: Numerous mortality prediction tools are currently available to assist patients
with moderate to severe traumatic brain injury (TBI). However, an algorithm that utilizes …

Individualized patient care is essential to reduce the global burden of traumatic brain injury
(TBI). This pilot study focused on TBI patients admitted to intensive care units (ICUs) and …

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 …

Secondary neurologic decline (ND) after traumatic brain injury (TBI) is independently
associated with outcome, but robust predictors of ND are lacking. In this retrospective …

Background Predicting functional outcome in critically ill patients with traumatic brain injury
(TBI) strongly influences end-of-life decisions and information for surrogate decision makers …