Latest AI and machine learning research in emergency medicine for healthcare professionals.
Inventory management in intensive care units (ICUs) plays a critical role in ensuring uninterrupted patient care, yet it remains an underprioritised component of healthcare operations. This narrative review explores current challenges and evidence-based strategies for optimising ICU supply chains. Issues such as unpredictable demand, manual stock tracking, procurement inefficiencies and limited st...
Dyspnea is a complex symptom measured using subjective patient-reported ratings. Continuous, automated dyspnea measurements are needed, especially in critical care and trauma settings with impaired patient communication. We prospectively enrolled 54 pulmonary rehabilitation subjects. Participants completed two treadmill walking trials, during which dyspnea measurements were collected at one-minute...
Osteoporotic vertebral fractures impair quality of life and increase both morbidity and mortality, yet they are largely preventable. Routine CT examin...
OBJECTIVES: To develop an MS-Res-AttU-Net-based deep learning framework for automatic measurement of vertebral compression ratio (VCR) on lumbar magne...
BACKGROUND: Intracerebral hemorrhage (ICH) remains associated with high mortality and treatment variability. Current workflows rely on fragmented imag...
PURPOSE OF REVIEW: Artificial intelligence (AI) tools for cervical cancer screening have proliferated, but modality-pooled accuracy estimates conflate...
Artificial Intelligence (AI) surrogate models offer a computationally efficient alternative to full-physics simulations, yet no existing datasets are ...
Rapidly expanding industrial activities, along with rising human living standards, contribute to the emission of emerging pollutants (EPs) that have b...
Emergency medicine has evolved from an emerging discipline to a formally recognised specialty across much of Asia over the past four decades. Adoption...
Artificial intelligence-based culture reading tools can potentially accelerate reading, improving reporting consistency in image-based interpretation,...
Aging-related metabolic dysregulation and vascular vulnerability contribute substantially to stroke susceptibility, yet subtype-specific metabolic sig...
OBJECTIVES: This study examined why artificial intelligence (AI)-based clinical decision support tools have had limited clinical translation in the em...
Accurately predicting binding affinity and toxicity is critical to drug discovery, offering the potential to reduce development costs and enhance safe...
BACKGROUND: Generative artificial intelligence (AI) systems are increasingly used for health information seeking, yet it remains unclear how the publi...
ChatGPT Health, an artificial intelligence feature launched by OpenAI in January 2026, integrates personal medical records and consumer health data in...
BACKGROUND: Heart failure (HF) readmissions remain common and costly, yet existing prediction models show limited clinical utility, particularly at th...
INTRODUCTION: Emergency EEG (emEEG) is increasingly used in the emergency department (ED), but its diagnostic yield remains uncertain. This protocol d...
BACKGROUND AND PURPOSE: Technological innovation has played a pivotal role in shaping trauma and orthopaedic surgery. This narrative review examines t...
Early identification of patients at risk of severe pneumonia during Omicron SARS-CoV-2 infection is critical for optimizing care and allocating resour...
INTRODUCTION: Emergency department overcrowding remains a critical global challenge, and artificial intelligence-driven clinical decision support syst...