Background Modern clinical care in intensive care units is full of rich data, and machine
learning has great potential to support clinical decision-making. The development of …

Outcome prognostication in comatose patients after cardiac arrest (CA) remains to date a
challenge. The major determinant of clinical outcome is the post-hypoxic/ischemic …

Purpose: Traumatic brain injury (TBI) generally causes mortality and disability, particularly in
children. Machine learning (ML) is a computer algorithm, applied as a clinical prediction tool …

Background Various prognostic models are used to predict mortality and functional outcome
in patients after traumatic brain injury with a trend to incorporate machine learning protocols …

Traumatic brain injury (TBI) results in disparate outcomes ranging from persistent disorders
of consciousness to symptom resolution. Despite the breadth and complexity of TBI …

Despite changes in guideline-based management of moderate/severe traumatic brain injury
(TBI) over the preceding decades, little impact on mortality and morbidity have been seen …

Objective The aim of this study was to investigate the clinical curative effect of hyperbaric
oxygen (HBO) treatment and its mechanism in improving dysfunction following traumatic …

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 …

There is a need for reliable predictors in patients with moderate to severe traumatic brain
injury to assist clinical decision making. We assess the ability of early continuous EEG …

Recently, speckle visibility spectroscopy (SVS) was non-invasively applied on the head to
monitor cerebral blood flow. The technique, using a multi-pixel detecting device (eg …