Emergency Medicine

Predicting intracranial aneurysm rupture risk and intervention outcomes using denoising-enhanced CT Angiography.

BACKGROUND AND PURPOSE: To develop a comprehensive multi-modal framework for assessing the rupture risk of intracranial aneurysms and predicting intervention outcomes. In addition, it seeks to a novel denoising algorithm to enhance the quality of CTA images, thereby improving morphological profiling. MATERIALS AND METHODS: This retrospective multicentre study included 352 patients who underwent CT...

Evaluation of an AI-Driven Risk Stratification System for Clinical Deterioration in Geriatric Hip Fracture Patients.

OBJECTIVES: To determine whether an artificial-intelligence-driven Clinical Deterioration Index (CDI) could identify geriatric hip-fracture patients at risk of early postoperative complications and to establish an orthopaedic-specific cutoff that identified patients at risk of deterioration. METHODS: Design: Retrospective cohort study. SETTING: Single Level I trauma center. PATIENT SELECTION CRITE...

Machine Learning-Based Risk Stratification for Symptomatic Intracranial Hemorrhage and 3-month Prognosis Following Intravenous Thrombolysis.

INTRODUCTION: Intravenous thrombolysis (IVT) with tissue-type plasminogen activator (tPA) is a cornerstone of acute ischemic stroke treatment, yet its...

Exploring the mechanism of Dieda Qili Tablet on fracture healing based on network pharmacology combined with machine learning models.

External validation of ECG artificial intelligence for emergency and cardiac assessment across a large-scale U.S. healthcare system.

An ECG-based artificial intelligence (AI) model was previously developed to generate ten digital biomarkers for emergency and cardiac assessment and i...

A Novel Triose Phosphate Isomerase Inhibitor With Dual Trypanosomicidal Activity was Identified Using Artificial Intelligence-Based Virtual Screening.

Chagas disease and leishmaniasis are neglected protozoan diseases recognized by the World Health Organization as major public health problems. These d...

Evaluation and enhancement of suspected opioid overdose definitions in emergency medical services data using machine learning with natural language processing.

BACKGROUND: Fatal and non-fatal drug overdoses have evolved into a critical public health crisis, with over a 50% increase in the rate of fatal drug o...

Personalizing anesthetic management in trauma patients using machine learning.

PURPOSE OF THE REVIEW: Artificial intelligence in health is evolving rapidly, and there is a lot of hope that it may improve patient outcomes. The per...

Does Sequential Use of Multiple Chatbots Influence Emergency Guidance for Dental Avulsion?

BACKGROUND/AIM: Artificial intelligence-based chatbot systems are increasingly used for dental emergency guidance, yet the clinical value of sequentia...

GAN-GA: A Deep-Evolutionary Approach for Synthesizing Functionally Similar Heat Shock Proteins.

De novo protein design has emerged as a transformative approach for generating functional proteins without relying on naturally occurring templates, o...

Integrating AI Into Governmental Public Health Decision Making: Challenges, Considerations, and a Path Forward.

Public health emergencies such as pandemics, natural disasters, and epidemics may require rapid, high-stakes decisions often made by elected officials...

The role of large language models in the diagnosis and management of obstetric patients: a pilot feasibility study using simulated obstetric cases.

OBJECTIVE: This feasibility study aimed to assess the potential of freely available large language models (LLMs) to support clinical decision-making i...

Artificial intelligence for detecting acute heart failure on chest CT: prospective clinical proof-of-concept validation.

OBJECTIVE: Acute heart failure (AHF) is a common but underrecognized cause of dyspnea. Chest computed tomography (CT) can accurately assess pulmonary ...

AI-assisted versus fully automated volumetry for hemorrhage quantification in spontaneous ICH with ventricular extension: A multi-center study.

BACKGROUND: Spontaneous intracerebral hemorrhage (sICH) with intraventricular hemorrhage (IVH) extension is a neurological emergency associated with h...

Machine Learning-Guided Optimization of Additively Manufactured TiB2-Modified Aluminum Alloys.

The rapid development of additive manufacturing (AM) offers unprecedented design freedom for high-performance aluminum alloys, yet process optimizatio...

Tech That Scales: A Practical Framework for Artificial Intelligence-Enabled Cancer Care in Low- and Middle-Income Countries and Underserved US Counties.

Cancer outcomes remain starkly unequal: 5-year survival rates for common malignancies in low- and middle-income countries (LMICs) often lag 20-40 perc...

Integrating network toxicology and experimental validation to elucidate the molecular mechanism basis of chondrotoxicity of Benzo[a]pyrene in osteoarthritis.

Benzo[a]pyrene (BaP), a widespread environmental pollutant, has been increasingly implicated in the pathogenesis of chronic degenerative diseases. Env...

Uncovering the Global Burden and Future Trajectories of Nanomagnetite Particle Emissions from Biomass Power Plants.

Biomass power plants (BPPs) are expanding rapidly, yet the most toxicologically potent nanoscale fraction of its particulate emissions remains poorly ...

Clinician interaction with a machine learning algorithm for the assessment of patients with possible acute heart failure: a qualitative study.

BACKGROUND: Machine learning (ML) could improve clinical decisions in patients with possible acute heart failure, but few studies have evaluated accep...

Preliminary development of a child physical abuse algorithm using emergency department records.

BACKGROUND: Victims of child physical abuse (CPA) disproportionately use the emergency department, yet identifying CPA remains challenging in this set...