Emergency Medicine

AI in clinical trials: Current status, challenges, and future directions for emergency infectious disease clinical trials -Insights from the 2025 iCROWN Symposium.

Artificial intelligence (AI) has the potential to transform how drug development and clinical trials are conducted. The 2025 Infectious Disease Clinical Research Network with National Repository (iCROWN) Symposium held in Japan on January 26, 2026 brought together experts from academia, industry, and research ethics to discuss current applications, limitations, and ethical considerations of AI in ...

Evaluating Guideline-Adherent Antibiotic Use for Skin Infections Using Natural Language Processing: A Pilot Study.

OBJECTIVE: To develop and evaluate an internally validated natural language processing (NLP) model to determine guideline adherence of antibiotic decisions in the emergency department (ED) for skin and soft tissue infections (SSTIs). METHODS: This cross-sectional pilot study developed and applied a random forest (RF)/NLP model to classify clinical narratives of patients with skin infections as req...

Virtual Control Groups in Nonclinical Research: A Re-analysis of 20 Studies Using Virtual Control Group Data.

Animal models are crucial in biomedical research, particularly in pharmaceutical discovery and safety testing. Recent legislative updates and regulato...

Artificial intelligence revolution in toxicology: Clinical precision, global equity, and the 2030 roadmap.

Artificial intelligence (AI) is transforming toxicology by enabling faster, more accurate, and more equitable approaches to diagnosis, treatment, rese...

A two-stage gradient boosting framework coupled with Lagrangian particle tracking for rapid atmospheric radionuclide dispersion prediction in nuclear emergency response.

Predicting the atmospheric dispersion of radionuclides is central to nuclear emergency response, yet any useful prediction tool must balance physical ...

Impact of Imaging Acquisition and Protocol Variability on Artificial Intelligence Model Performance: A Secondary Analysis of the ASFNR Artificial Intelligence Competition.

BACKGROUND AND PURPOSE: Artificial intelligence (AI) models have shown promise in neuroradiology, yet their real-world generalizability remains uncert...

Constraint optimization and key factor analysis based vehicle emergency braking strategy generator.

Enhancing vehicle emergency braking performance is crucial for vehicular safety and reliability. We have observed that the traditional vehicle dynamic...

Remote sensing and geochemical constraints on polymetallic mineralization in Abu Rusheid and Sikait granites of Egypt.

The post-tectonic granites and pegmatites of the Abu Rusheid-Sikait area, in the South Eastern Desert of Egypt, represent highly mineralized plutons w...

Advancing medical AI through benchmarking and competition for specialty triage.

Artificial intelligence holds transformative potential for clinical triage, yet challenges in accuracy, generalization, and interpretability persist. ...

Elucidating the mechanisms of aristolochic acid-induced upper tract urothelial carcinoma: A multi-omics approach combining bioinformatics and computational modeling.

Aristolochic acids (AAs) are established human carcinogens strongly associated with upper tract urothelial carcinoma (UTUC). However, the multi-target...

Machine learning models to detect opioid misuse in emergency department patients at triage.

OBJECTIVE: Emergency department (ED) encounters represent valuable opportunities to initiate evidence-based treatments for patients with opioid misuse...

Deep Learning Model to Detect Diabetic Retinopathy in 45° Images Using Ground Truth from Ultra-Widefield Imaging.

PURPOSE: To evaluate the performance of a deep learning (DL) model in classifying diabetic retinopathy (DR) severity using fundus images with varying ...

Molecular basis of muscle wasting and emerging therapeutic strategies targeting degenerative muscle disorders.

Muscle degenerative conditions, including sarcopenia, muscular dystrophies, and trauma-induced muscle loss, severely compromise mobility, metabolism, ...

AATE-UNet automated assessment of inflammatory response in zebrafish larvae exposed to environmental risks.

In the evaluation of drugs/cosmetics toxicology/efficacy on livings, rapid assessment of inflammatory responses in zebrafish models is critical but hi...

Using Data and Artificial Intelligence to Improve Care Pathways of Older People Experiencing Falls and Frailty: Opportunities, Challenges, and Practical Considerations for Clinicians.

Older people living with falls and frailty are common in emergency attendances, admissions and functional decline. Artificial intelligence (AI) and ma...

Exploring key risk factors for loss to follow-up after hospitalization for acute stroke.

BACKGROUND: A significant proportion of stroke patients are lost to follow-up (LTFU) after discharge, which may increase risks of morbidity, mortality...

Domain-Shift AI Technology for Vendor-Agnostic Multiple Macular Disease Detection From 3D OCT Scans.

IMPORTANCE: A deep learning (DL) model capable of analyzing optical coherence tomography (OCT) 3-dimensional (3D) scans from various vendors is essent...

Effects of a Semantically Irrelevant Virtual Reality Experience on Memory and Emotion After Watching a Traumatic Event: Randomized Controlled Experimental Study.

BACKGROUND: First responders, such as firefighters, experience significant mental health issues due to the high-stress nature of their work. Existing ...

A novel statistical framework for quantifying risks and benefits of AI automation in screening mammography.

AI has been proposed as a triage or "rule-out" device to reduce radiologist workload, but it is presently unclear how an AI "rule-out" threshold shoul...

Artificial intelligence in emergency musculoskeletal imaging: A critical review of current applications.

Artificial intelligence (AI) is increasingly shaping emergency musculoskeletal imaging, where rapid and accurate diagnosis is often challenged by high...