Emergency Medicine

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 p...

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 ...

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,...

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 w...

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 fo...

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 extracor...

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...

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 resou...

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 (C...

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, ...

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

Cardiogenic shock (CS) remains a major clinical challenge, with persistently high short-term mortali...

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 depend...

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

Detecting multimorbidity patterns in Alzheimer's disease using unsupervised machine learning: A nationwide emergency department study (2007-2022).

BackgroundAlzheimer's disease (AD) patients frequently present to emergency departments (EDs) with c...

Artificial intelligence for diagnosis and triage in oral cancer: a clinician‑centered narrative review.

BACKGROUND: Early diagnosis of oral squamous cell carcinoma (OSCC) remains challenging, with surviva...

Impurities in Oncology Pharmaceuticals: A Review of Classification, Detection Methods, Regulatory Frameworks and Emerging Trends.

Pharmaceutical impurities pose a significant challenge in the development and manufacturing of anti-...

Multi-omics investigation of benzo[a]pyrene in gastric cancer: comprehensive network toxicology, machine learning and molecular docking approaches.

Gastric cancer (GC) risk is shaped by environmental exposures such as benzo[a]pyrene (BaP). Here, we...

Strategic Governance of Artificial Intelligence-Enabled Clinical Algorithm Development: Formative Evaluation of the Semiautomatic Clinical Algorithm Development Framework.

BACKGROUND: Health care leaders face a strategic dilemma: traditional expert-led content development...

CT-based hybrid deep learning-radiomics framework for predicting postoperative rebleeding in hypertensive intracerebral hemorrhage.

OBJECTIVES: Hypertensive intracerebral hemorrhage (HICH) is a frequently encountered and highly leth...

Deep-Fed: A comprehensive solution for precise bone fracture identification in athletes.

Bone fracture diagnosis is a critical aspect of sports medicine, where accurate and timely detection...

Exploring the mechanism of polymorphonuclear neutrophils against sepsis based on immune model.

BACKGROUND: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to...