Latest AI and machine learning research in emergency medicine for healthcare professionals.
BACKGROUND: Artificial intelligence (AI) offers transformative potential for clinical care, yet its deployment in conflict-affected, low-resource settings remains under-researched. This study evaluates AI awareness, barriers, and readiness among Sudanese surgeons amidst the nation's ongoing armed conflict. METHODS: A sequential explanatory mixed-methods design was employed. An online survey, adapt...
BACKGROUND: Delayed cerebral ischemia (DCI) remains a major morbidity and mortality problem following aneurysmal subarachnoid hemorrhage (SAH). Advancements in neurocritical care permit a slow but accurate identification of patients at high risk for DCI. Machine learning models are now emerging as tools for DCI prediction that may provide more individualized risk assessment than conventional appro...
INTRODUCTION: Hemorrhagic shock is the most common preventable cause of death in trauma patients. Early transfusion significantly improves survivabili...
OBJECTIVE: To comparatively evaluate the clinical responses of three digital platforms (ChatGPT 5.2, DeepSeek, Consensus) in terms of responsiveness, ...
Limited proteolysis coupled to mass spectrometry (LiP-MS) probes protein conformational dynamics, but interpretation of LiP-MS data is complicated by ...
The Kingdom of Saudi Arabia has been making significant progress as part of its Vision 2030 to diversify its economy and reduce dependence on fossil f...
PURPOSE: Chest X-rays (CXRs) are essential in trauma care but have limited sensitivity for rib fracture detection, leading to frequent missed diagnose...
Understanding the complex chemistry of organic materials under dynamic compression is important for many applications, but it is challenging due to th...
Heat shock protein 90 (Hsp90) is a key cancer drug target, yet the highly flexible N-terminal ATP-binding pocket yields seemingly conflicting crystall...
Microplastic (MP) pollution is a growing global concern with serious implications for ecosystems and human health. The present review provides a compr...
BACKGROUND: Pediatric cardiopulmonary resuscitation (CPR) is a highly complex and time-critical process that demands precise team coordination and str...
Artificial intelligence (AI) embedded in point-of-care ultrasound (POCUS) could reduce operator dependence in left ventricular ejection fraction (LVEF...
BACKGROUND: There has been a growing interest in the clinical application of artificial intelligence (AI) tools in medical imaging to aid diagnosis. T...
AIMS: The role of electrocardiography (ECG) has been limited in the preoperative risk evaluation in noncardiac surgery due to its low prognostic value...
OBJECTIVES: To describe the structured process of threshold optimisation for a commercially available multiclass chest X-ray (CXR) deep learning model...
Systemic barriers, including language, navigation complexity, and long specialist wait-times, result in the under-utilization of mental health service...
BACKGROUND: Mechanical thrombectomy (MT) improves outcomes in acute ischemic stroke (AIS) but often results in hyperdensities on non-contrast CT (NCCT...
Chronic and subchronic toxicity are very important endpoints for evaluating the long-term and medium-term toxicity of chemical substances. However, du...
Develop and evaluate whether a model trained to detect the physiological signature of hemorrhage in ICU patients generalizes to other cohorts. App...
The men and women who worked in rescue and recovery operations at the 9/11 World Trade Center site are developing cognitive impairment (CI) at mid-lif...