Artificial intelligence (AI), a branch of machine learning (ML) has been increasingly
employed in the research of trauma in various aspects. Hemorrhage is the most common …

Artificial intelligence (AI) and machine learning describe a broad range of algorithm types
that can be trained based on datasets to make predictions. The increasing sophistication of …

A deep learned recurrent type-3 (RT3) fuzzy logic system (FLS) with nonlinear consequent
part is presented for renewable energy modeling and prediction. Beside the rule …

Machine Learning holds promise for actionable decision support in trauma science, but
rigorous proof-of-concept studies are urgently needed. Future research should assess …

Blood transfusion is a routine medical procedure in hospitals with over 2 million blood
products transfused in the UK every year at a cost of over£ 300 million and a median …

Background It remains unclear whether the association between balanced blood component
transfusion and lower mortality is generalizable to trauma patients receiving varying …

Our scoping review provides a comprehensive analysis of the landscape of artificial
intelligence (AI) applications in prehospital emergency care (PEC). It contributes to the field …

Background Tiered trauma triage systems have resulted in a significant mortality reduction,
but models have remained unchanged. The aim of this study was to develop and test an …

Background Though artificial intelligence (“AI”) has been increasingly applied to patient
care, many of these predictive models are retrospective and not readily available for real …

Hemorrhage is the leading cause of preventable death from trauma. Traditionally, vital signs
have been used to detect blood loss and possible hemorrhagic shock. However, vital signs …