Emergency Medicine

Clinical Management of Wasp Stings Using Large Language Models: Cross-Sectional Evaluation Study.

BACKGROUND: Wasp stings are a significant public health concern in many parts of the world, particularly in tropical and subtropical regions. The venom of wasps contains a variety of bioactive compounds that can lead to a wide range of clinical effects, from mild localized pain and swelling to severe, life-threatening allergic reactions, such as anaphylaxis. With the rapid development of artificia...

Multimodal deep learning for chemical toxicity prediction and management.

The accurate prediction of chemical toxicity is a crucial research focus in chemistry, biotechnology, and national defense. The development of comprehensive datasets for chemical toxicity prediction remains limited due to security constraints and the structural complexity of chemical data. Existing studies are often confined to specific domains, such as genotoxicity or acute oral toxicity. To addr...

A Machine Learning Trauma Triage Model for Critical Care Transport.

IMPORTANCE: Under austere prehospital conditions, rapid classification of injured patients for intervention or transport is essential for providing li...

A hybrid PSO-FFNN approach for optimized seismic design and accurate structural response prediction in steel moment-resisting frames.

The first steel is the most prevalent material used in building. Steel's intrinsic hardness and durability make it appropriate for different uses, but...

An Appraisal of the Quality of Development and Reporting of Predictive Models in Spine Surgery.

Study DesignLiterature review.ObjectiveThe Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) st...

Neuromethods: Basic Techniques for Evaluating the Nervous System in Nonclinical Studies.

The first session of the 2025 European Society of Toxicologic Pathology (ESTP) Congress reviewed routine and specialized methods for microscopic evalu...

Stroke Sensitivity Calculation in Medical Emergency Calls and Factors Associated With Stroke Suspicion: A Retrospective Registry-Based Study.

STUDY OBJECTIVE: Sensitivity for stroke detection in emergency medical communication centers (EMCCs) varies widely. Few studies offer detailed insight...

Forecasting Hospitalization for Adult Asthma Patients in Emergency Departments Based on Multiple Environmental and Clinical Factors.

BACKGROUND: Asthma is the world's second most prevalent chronic respiratory disease. Current clinical decisions regarding hospitalization for adult as...

Systematic Exploration of Potential Toxicity Targets and Molecular Mechanisms of Emerging Short-Chain PFAS Substitutes: PFBA- and PFBS-Induced Hepatocellular Carcinoma Based on Toxicity Network Analysis, Machine Learning, and Biomimetic Calculations.

Perfluorobutanoic acid (PFBA) and perfluorobutanesulfonic acid (PFBS) are short-chain alternatives to traditional perfluoroalkyl and polyfluoroalkyl s...

Advancing Musculoskeletal Care Using AI and Digital Health Applications: A Review of Commercial Solutions.

Artificial intelligence (AI) and digital health (DH) solutions are reshaping musculoskeletal (MSK) care across diagnostics, treatment planning, workfl...

From Fragile Lives to Forensic Truth: Multimodal Forensic Approaches to Pediatric Homicide and Suspect Death.

Forensic investigation of child homicides presents unique challenges due to the vulnerability of children and the complexity of distinguishing betwee...

Predicting the Higher Energy Need for Effective Defibrillation Using Machine Learning Based on an Animal Model.

: Early defibrillation improves outcomes in cardiac arrest, but the optimal defibrillation strategy and energy requirements remain debated. This study...

Can artificial intelligence improve the diagnosis and prognosis of disorders of consciousness? A scoping review.

BACKGROUND: Artificial intelligence (AI), in the form of machine learning (ML) or deep learning (DL) models, can aid clinicians in the diagnostic proc...

A Novel and Modern Calculator to Predict Vaginal Birth after Cesarean Delivery.

Counseling patients who are considering a trial of labor after cesarean (TOLAC) is a challenging task given the risks and benefits of either approach....

Development and validation of a machine learning-based model for predicting intraoperative blood loss during burn surgery.

BACKGROUND: Intraoperative blood loss is a critical issue in the care of patients with burns. The timely identification of patients at elevated risk f...

Dental Trauma Evo - Development of an Artificial Intelligence-powered Chatbot to Support Professional Management of Dental Trauma.

INTRODUCTION: Dental trauma is a public health issue that requires proper clinical management to minimize complications. Artificial intelligence-based...

Association between the stress hyperglycemia ratio and all-cause mortality in patients with hemorrhagic stroke: a retrospective analysis based on MIMIC-IV database.

BACKGROUND: Research on the associations between the stress hyperglycemia ratio (SHR) and adverse outcomes in patients with hemorrhagic stroke is limi...

Gasdermin D drives the systemic storm and mortality after trauma with hemorrhage to a greater degree in biological females than males.

Severe injury accompanied by hemorrhagic shock triggers an early release of cell constituents into the circulation, referred to as the systemic storm....

Digital Technology Prediction of Anger, Aggression, and Violence: Recent Innovations and Methodological Considerations.

Data derived from smartphone and wearable devices, combined with artificial intelligence/machine learning, have great potential to predict, detect, an...

Artificial Intelligence in Value-Based Health Care.

Artificial intelligence (AI) presents new opportunities to advance value-based healthcare in orthopedic surgery through 3 potential mechanisms: agency...