Latest AI and machine learning research in emergency medicine for healthcare professionals.
AIMS: To develop, deploy and evaluate artificial intelligence (AI) for triaging duodenal biopsies within a National Health Service (NHS) histopathology laboratory, with the aim of improving reporting turnaround times for clinically significant diagnoses. METHODS: The pathway was developed in the UK in an NHS laboratory. Rule-based automation software was used to find all newly scanned duodenal bio...
Large-core anterior circulation ischemic stroke (LCIS) complicated by malignant cerebral edema (MCE) remains a leading cause of early death and profound disability even in the era of endovascular thrombectomy (EVT). As EVT indications have expanded to include patients with large ischemic cores, more patients survive the initial ischemic insult but continue to face substantial risk of space-occupyi...
Wound healing is a dynamic and highly coordinated biological process involving hemostasis, inflammation, proliferation, and tissue remodeling. However...
PURPOSE: To estimate the associations of prevalent vertebral fracture (PVFx) and abdominal aortic calcification (AAC) with incident ASCVD (myocardial ...
BACKGROUND: Conflict zones severely disrupt healthcare access, with millions affected by armed conflicts. The lack of standardized medical guidance ex...
BACKGROUND: The Pediatric Assessment Triangle (PAT) is a rapid visual assessment framework designed to support early identification of critically ill ...
OBJECTIVE: Rapid advancements in artificial intelligence (AI) technologies offer new opportunities in medical education. The aim of this study is to c...
BACKGROUND: Overdose rates in the U.S. rose dramatically during the COVID-19 pandemic. Well-documented racial and sociodemographic inequities in the i...
Most existing intracranial hematoma segmentation models target acute hemorrhages and may not generalize to the heterogeneous morphology of chronic sub...
The Urgent and Emergency Care system generates a wealth of clinical information, but our ability to harness this for public health planning and to add...
Ethyl maltol is a ubiquitous synthetic flavor enhancer. Despite its widespread use in foods, beverages, and electronic cigarettes, and its potential f...
High-entropy materials (HEMs) represent a paradigm shift in developing efficient components of proton exchange membrane fuel cells/water electrolysis ...
BACKGROUND: Self-harm, defined as non-fatal self-inflicted harm regardless of suicidal intent, is a critical global health issue influenced by the int...
OBJECTIVES: Early sepsis and stroke recognition by emergency medical services (EMS) improves triage, treatment, and patient outcomes. Machine learning...
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease is highly prevalent in adults with type 2 diabetes, and advanced fibrosis is its ...
Accurate and rapid delineation of diffuse gliomas is essential in emergency neuro-oncology, yet MRI is often unavailable. We present a deep-learning s...
BACKGROUND: AI-based burn depth assessment is rapidly emerging, yet evidence for diagnostic accuracy, generalizability, and deployment readiness remai...
Dyspnea is the subjective sensation of breathing discomfort. This symptom is highly prevalent in patients with chronic and critical illness, and its p...
Imaging after ischemic and hemorrhagic stroke may allow measurement of key phenotypes of injury and recovery for which targeted therapies are still la...
Machine learning has the potential to address limitations of traditional osteoporosis screening through advanced data processing and pattern recogniti...