Latest AI and machine learning research in emergency medicine for healthcare professionals.
Although the prevalence of autism spectrum disorder (ASD) has risen sharply in the last few years re...
A large quantity of high throughput screening (HTS) data for antimalarial activity has become availa...
Understanding the processes of mitochondrial dynamics (fission, fusion, biogenesis, and mitophagy) h...
Adverse drug reactions (ADRs) are noxious and unexpected effects during normal drug therapy. They ha...
BACKGROUND: Modeling drug interactions is important for illustrating combined drug actions and for p...
OBJECTIVES: (1) To develop an automated eligibility screening (ES) approach for clinical trials in a...
OBJECTIVE: Half of all adult emergency department (ED) visits with a complaint of dyspnea involve ac...
While machine learning has gained traction in toxicological assessments, the limited data availabili...
Patients often use Google for their medical questions. With the emergence of artificial intelligence...
This study evaluates fine-tuned Llama 3.2 models for extracting vaccine-related information from eme...
Chemical oxidation is pivotal in remediating organic pollutants in aquatic systems; however, it freq...
Dengue pathogenesis involves immune-driven inflammation that contributes to severe disease progressi...
Per- and polyfluoroalkyl substances (PFAS), due to their recalcitrance, toxicity, and widespread env...
PURPOSE OF REVIEW: Temporary circulatory support (TCS) devices play a crucial role in stabilizing pa...
Health literacy is essential in patient care, especially in burn treatment, where understanding care...
Screening chemicals using the zebrafish embryo developmental toxicity assay requires visual assessme...
The potential of Artificial intelligence (AI) is increasingly recognized in musculoskeletal radiolog...
Cell-based bioassays provide a dynamic and physiologically relevant platform for investigating cellu...
Stroke remains a leading cause of death and disability worldwide. While well-established risk factor...
The integration of large language models (LLM) into the care of trauma surgery patients offers an ex...
BACKGROUND: Triage aims to prioritize patients according to their medical urgency by accurately eval...