Emergency Medicine

Closed-loop and Artificial intelligence guided cardiopulmonary resuscitation using real-time physiological signals: a systematic review and meta-analysis.

BACKGROUND: Current cardiopulmonary resuscitation (CPR) includes breaks to check rhythm and pulse, while high-quality CPR requires continual chest compressions. Artificial intelligence (AI)-driven "closed-loop" or "near-closed-loop" systems may evaluate CPR-contaminated signals, guide shock and pulse decisions. METHODS: According to PRISMA statement 2020, We searched databases from 2010 to 2025 fo...

Artificial intelligence in the diagnosis and prognosis of ocular trauma: a systematic review.

Low atherogenic index of plasma is associated with spontaneous hemorrhagic transformation in acute ischemic stroke patients: a retrospective cohort study and predictive modeling based on machine learning.

Unraveling the potential carcinogenic risk of bisphenols: a comprehensive network analysis and computational toxicology insights.

Dietary exposure to antimicrobial residues in eggs: Traceability-driven risk heterogeneity and national monitoring optimization in China.

Egg production is growing rapidly to meet global protein demand, but in low- and middle-income countries, heavy antimicrobial use, fragmented supply c...

The Future of Artificial Intelligence in Emergency Medical Services by 2030: An International Consensus Report.

OBJECTIVES: Artificial intelligence (AI) is an application of digital technology with considerable potential to improve quality, safety, and access; h...

Global distribution, pathogen spectrum, and invasion potential of Hyalomma anatolicum at the human-livestock interface: A systematic review, meta-analysis, and ecological niche modeling.

Hyalomma anatolicum is an efficient vector at the human-livestock interface, yet its global ecological profile remains insufficiently defined. This st...

Evaluating the Performance of Large Language Models for Generating Emergency Department Discharge Instructions.

BACKGROUND: Clear discharge instructions are essential for safe emergency department (ED) care, yet creating patient-centered, health literate materia...

Use of artificial intelligence and radiomics for diagnosis and prediction of osteoporotic fractures: a systematic review.

AIM: Osteoporosis (OP) is a prevalent metabolic bone disease causing millions of fractures annually, leading to significant healthcare and economic bu...

Assessing the impact of groundwater abstraction and concrete dam fractures on saltwater intrusion using numerical modeling and interpretable machine learning.

Reliable prediction of SWI is essential for protecting coastal groundwater. In this study, the SWI wedge length in a sloping coastal aquifer controlle...

Accurate, fair, and generalisable scaling of injury severity score-based AI with demographics in terms of mortality in patients with trauma: multi-centre, multi-national retrospective cohort study.

BACKGROUND: Accurate and equitable prediction of trauma-related in-hospital mortality is critical for guiding clinical decisions and optimising trauma...

Acid-Base Status During Venoarterial Extracorporeal Membrane Oxygenator Support in Patients With Cardiogenic Shock.

BACKGROUND: The prognostic significance of an adverse acid-base milieu despite venoarterial extracorporeal membrane oxygenation support in patients wi...

Integrated network toxicology and computational profiling of acetyl tributyl citrate-related mechanisms in Alzheimer's disease.

BackgroundAcetyl tributyl citrate (ATBC), an eco-friendly plasticizer, exhibits poorly characterized neurotoxic effects.ObjectiveWe integrated network...

Forecasting emergency department visits in the reference hospital of the Balearic Islands: The role of tourist and weather data.

Accurate forecasting of patient arrivals at emergency departments (EDs) is vital for efficient resource allocation and high-quality patient care. In t...

A complete blood count-based machine learning model for rapid differentiation of aplastic anemia, immune thrombocytopenia, and myelodysplastic syndromes in routine clinical practice.

BACKGROUND: Accurate differentiation of common hematologic disorders remains challenging in routine clinical practice and often requires invasive diag...

Development and temporal validation of an interpretable point score for in-hospital mortality in CLL/SLL using the U.S. National Inpatient Sample, 2016-2022.

In-hospital mortality among patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) is ∼6%, yet no validated, transparent beds...

Evidence-based AI clinical decision support system for acute burn care and complex reconstruction.

BACKGROUND: Burn surgery requires rapid, evidence-based decision-making across acute resuscitation, operative management, and reconstruction. Despite ...

Cardiogenic Shock Revisited: From Hemodynamic-Centric to Multimodal Precision Care.

Cardiogenic shock (CS) remains a major clinical challenge, with persistently high short-term mortality despite advances in reperfusion therapy, pharma...

LLM-based keyword augmentation for title-driven evidence selection: A practical approach.

Keyword-based search is widely used in digital forensic investigations, yet its effectiveness depends strongly on investigator experience, leading to ...

Can algorithms come to the rescue of a failing heart? Machine learning, artificial intelligence, and decision-making in cardiogenic shock.