Latest AI and machine learning research in emergency medicine for healthcare professionals.
Identifying brain hemorrhages from magnetic resonance imaging (MRI) is a critical task for healthc...
Pain assessment is a critical aspect of medical care, yet automated systems for clinical pain estima...
Inherited platelet disorders (IPDs) are rare conditions with diverse underlying pathophysiology whic...
The integration of large language models (LLM) into the care of trauma surgery patients offers an ex...
Patients with intracerebral hemorrhage (ICH) are highly susceptible to sepsis. This study evaluates ...
Quantitative structure-activity relationship (QSAR) models are essential for predicting endpoints th...
This study aims to predict hemorrhagic stroke outcomes, including 90-day prognosis and in-hospital m...
BACKGROUND: Mobile health (mHealth) applications (apps) integrated with artificial intelligence for ...
The safety of autonomous cars has come under scrutiny in recent years, especially after 16 documen...
Accurate diagnosis of orthopedic injuries, especially pelvic and hip fractures, is vital in trauma m...
The integration of machine-learning technologies into radiology practice has the potential to signif...
OBJECTIVE: To develop an early budget impact analysis of and inform future research on the national ...
Harmonization of T1-weighted MR images across different scanners is crucial for ensuring consisten...
Sepsis, septic shock, and cardiogenic shock are life-threatening conditions associated with high mor...
Inland water body segmentation from Synthetic Aperture Radar (SAR) images is an important task nee...
The goal of segmentation in abdominal imaging for emergency medicine is to accurately identify and d...
Triage is used in emergency departments to ensure timely patient care according to urgency of treatm...
Accurately predicting the pharmacological and toxicological properties of molecules is a critical st...
Forcing ChatGPT and other large language models to perform roles reserved for physicians and other h...
To evaluate the accuracy of a Bidirectional Encoder Representations for Transformers (BERT) Natural...
Purpose To develop and evaluate machine learning and deep learning-based models for automated protoc...