Latest AI and machine learning research in emergency medicine for healthcare professionals.
BACKGROUND: Clinical triage requires integrating multiple information sources to identify patients at risk of deterioration. Tools capturing global health assessments beyond disease-specific scores are being developed using either bottom-up aggregation of simple indicators or top-down machine learning from large datasets. Their alignment with expert clinical judgment remains poorly characterized. ...
BACKGROUND: Acromial and scapular spine fractures (ASSF) are an uncommon but significant complication following reverse total shoulder arthroplasty (rTSA). The study aims were to (1) determine the incidence and type of ASSF captured within a local shoulder arthroplasty registry, (2) develop a novel, interpretable machine learning model to predict individual risk of fracture after rTSA and (3) asse...
BACKGROUND: Tuberculosis (TB) remains a major health threat in prisons, where overcrowding and limited access to care facilitate transmission. We eval...
BACKGROUND: Depression is a major global public health burden, and environmental pollutants are increasingly associated with depressive symptoms. Vola...
BACKGROUND: A discharge summary should be a clinical report that documents a patient's hospital stay, including test results, diagnoses, management, a...
BACKGROUND: Wrist fractures are prevalent, and the diagnostic performance of artificial intelligence for their detection requires clarification. This ...
BACKGROUND: Artificial intelligence (AI) is increasingly penetrating health and dental fields without sufficient monitoring of its quality and applica...
Exposure to trauma and mild traumatic brain injury (mTBI), which often co-occur and can both trigger acute and chronic pathophysiological processes, h...
BACKGROUND: Pneumothorax is a finding that is frequently missed in the emergency department, particularly in cases with subtle radiographic features, ...
Inhaled aerosol dosimetry is a critical discipline bridging exposure to biological effect in both therapeutic and toxicological contexts. This review ...
BackgroundArtificial intelligence (AI) and machine learning are transforming neurosurgical research and practice, yet the programming barrier has excl...
Magnetic resonance imaging (MRI) at low magnetic field strengths (under 1 T) has seen renewed interest, driven by technological advances that enhance ...
Per- and polyfluoroalkyl substances (PFAS) are highly persistent synthetic chemicals that are widely detected in environmental and biological systems ...
AIMS: The rapid integration of genetics into clinical care and research has outpaced the supply of genetic professionals, creating persistent challeng...
BACKGROUND: Clinician burnout has reached crisis levels in emergency medicine, with clinical documentation burden identified as a central contributing...
BACKGROUND: Ensuring accuracy and consistency in emergency department (ED) triage is vital to patient safety. Despite the presence of standardized pro...
Carcinogenicity evaluation is a critical component of chemical risk assessment, yet traditional in vivo testing remains time consuming, costly, and et...
2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), a highly toxic persistent organic pollutant (POP), is associated with musculoskeletal disorders, yet its m...
Physics-aware recurrent convolutional networks (PARC) have demonstrated strong performance in predicting nonlinear spatiotemporal dynamics by embeddin...
Following lower limb trauma, performing orthopaedic rehabilitation exercises is a crucial factor in successful recovery. However, many patients find i...