Latest AI and machine learning research in emergency medicine for healthcare professionals.
Postpartum hemorrhage (PPH) is a major cause of maternal morbidity and mortality. Timely prediction ...
Pre-procedural risk prediction of 30-day all-cause mortality after percutaneous coronary interventio...
Effective clinical decision-making in critical care depends on interpreting complex, high-dimensiona...
To evaluate the performance of leading Large Language Models (LLMs) in classifying suicide risk and ...
Representatives of the trauma community have voiced a need for a new approach to developing clinical...
Artificial intelligence (AI) and statistical models designed to predict same-admission outcomes for ...
In this study, we developed ML algorithms to predict fragility fractures, considering the occurrence...
Opioid misuse remains a critical public health concern, associated with increased risk of overdose, ...
Pelvic fractures have consistently been a focal point in orthopedic research. This study aims to pro...
Resource Constrained Situations (RCS) at Emergency Medical Dispatch centers where there are more pat...
To evaluate convolutional neural network (CNN) model training strategies that optimize the performan...
Acute ischemic stroke (AIS) management has evolved substantially over the past two decades, with mec...
Hematoma expansion is a consistent predictor of poor neurological outcome and mortality after sponta...
Atrial fibrillation (AF) is a prevalent condition in emergency department (ED) patients and is assoc...
One in 25 deaths worldwide is related to liver disease, and often with multiple hepatosplenic condit...
Cardiogenic shock (CS) is a severe and frequent complication of acute myocardial infarction (AMI), n...
Conversational agents based on large language models (LLMs) have shown moderate efficacy in reducing...
Extending our validated benchmarking work, GPT-5 showed no improvement in sociodemographic-linked de...
Malaysia faces a significant burden of breast cancer, compounded by a chronic shortage of pathologis...
The aim of this study was to test whether open-source Large Language Models (LLMs) can match the dia...
Missed opportunities for diagnosis (MODs), sometimes termed diagnostic errors, are a major cause of ...