Emergency Medicine

Machine learning-assisted risk assessment for fluoroquinolone treatment in Chryseobacterium indologenes bacteremia: A comparative study of model performance and clinical calibration.

INTRODUCTION: Chryseobacterium indologenes bacteremia poses significant therapeutic challenges due to intrinsic multidrug resistance and the absence of established Clinical and Laboratory Standards Institute breakpoints for fluoroquinolones. We aimed to develop machine learning models to predict mortality and guide fluoroquinolone treatment decisions. METHODS: In this retrospective study of 61 pat...

Implementation of an ai-enabled multimodal emergency care system is associated with improved sudden cardiac death rescue outcomes in anyang.

Sudden Cardiac Death (SCD) remains a leading cause of mortality worldwide, with outcomes critically dependent on the effective implementation of the "Chain of Survival" - early recognition, early CPR, early defibrillation, and post-resuscitation care. In regional and pre-hospital settings, systemic fragmentation between emergency dispatch, ambulance services, and hospitals undermines this chain. T...

DeepTriage-CN: integrating clinical text with vital signs for emergency department admission prediction in an aging population.

Emergency department (ED) triage of older adults is challenging because standard early warning scores are often insensitive to atypical presentations....

Hierarchical multi-instance learning for targeted triage and classification of common left-to-right shunt lesions from echocardiography videos.

BACKGROUND: Transthoracic echocardiography is the first-line test for congenital heart disease (CHD), but accurate targeted triage and lesion subtypin...

Network toxicology and multi-omics identify potential interactions between between air pollutants and interferon-related signaling in tuberculosis.

BACKGROUND: Air pollution increases tuberculosis (TB) susceptibility, yet the underlying molecular mechanisms remain elusive. METHODS: We integrated h...

Graph Network Feature Space Fusion for Predicting Irregularly Sampled Medical Time-Series Data: Deep Learning Model Development and Validation Study.

BACKGROUND: Irregularly sampled data, as a common data structure in the medical field, is frequently observed in emergency clinical datasets. It poses...

Evaluation and Comparison of Latent Health Risk Prediction Models for Clinical Triage: Protocol for a Mixed Methods Study.

BACKGROUND: Clinical triage requires integrating multiple information sources to identify patients at risk of deterioration. Tools capturing global he...

Prediction of Acromial and Scapular Spine Fractures After Reverse Total Shoulder Arthroplasty using Machine Learning: A Retrospective Cohort Study.

BACKGROUND: Acromial and scapular spine fractures (ASSF) are an uncommon but significant complication following reverse total shoulder arthroplasty (r...

Screening for tuberculosis in prisons: efficacy of a breath-based diagnostic approach in a high prevalence setting.

BACKGROUND: Tuberculosis (TB) remains a major health threat in prisons, where overcrowding and limited access to care facilitate transmission. We eval...

Urinary Volatile Organic Compound Metabolites and Depressive Symptoms Among U.S. Adults With Cardiovascular-Kidney-Metabolic Syndrome Stages 0-3: NHANES-Based Associations and In Silico Multi-Omics Insights.

BACKGROUND: Depression is a major global public health burden, and environmental pollutants are increasingly associated with depressive symptoms. Vola...

Real-World Implementation of Large Language Models for Writing Clinical Discharge Summaries Within a Secure Data Environment: Development and Expert Evaluation Study.

BACKGROUND: A discharge summary should be a clinical report that documents a patient's hospital stay, including test results, diagnoses, management, a...

Meta-analysis and Systematic Review of Diagnostic Performance of Machine Learning Algorithms on Skeletally Mature Wrist Fractures.

BACKGROUND: Wrist fractures are prevalent, and the diagnostic performance of artificial intelligence for their detection requires clarification. This ...

Can AI chatbots be reliable in dental emergencies? quality assessment of Arabic responses to dental emergency inquiries and public attitudes toward their use.

BACKGROUND: Artificial intelligence (AI) is increasingly penetrating health and dental fields without sufficient monitoring of its quality and applica...

Artificial intelligence as a second reader for pneumothorax detection: redirecting rather than reducing chest CT use.

BACKGROUND: Pneumothorax is a finding that is frequently missed in the emergency department, particularly in cases with subtle radiographic features, ...

Dosimetry of Inhaled Aerosols: From Exposure to Target Tissue Dose in Risk Assessment and Drug Delivery.

Inhaled aerosol dosimetry is a critical discipline bridging exposure to biological effect in both therapeutic and toxicological contexts. This review ...

Vibe Coding in Neurosurgery: Bridging the Gap Between Clinical Needs and Digital Innovation-A Narrative Review and Practical Perspective.

BackgroundArtificial intelligence (AI) and machine learning are transforming neurosurgical research and practice, yet the programming barrier has excl...

Low-Field Neuroimaging: Opportunities and Limitations.

Magnetic resonance imaging (MRI) at low magnetic field strengths (under 1 T) has seen renewed interest, driven by technological advances that enhance ...

PFASGroups: An Open-Source Framework for Automated Identification, Structural Classification, and Prioritization of Per- and Polyfluoroalkyl Substances.

Per- and polyfluoroalkyl substances (PFAS) are highly persistent synthetic chemicals that are widely detected in environmental and biological systems ...

The impact of the rise of the chatbots: transforming genetics clinical delivery and research.

AIMS: The rapid integration of genetics into clinical care and research has outpaced the supply of genetic professionals, creating persistent challeng...

Ambient AI Scribes and Emergency Department Documentation Burden: Retrospective Cohort Study.

BACKGROUND: Clinician burnout has reached crisis levels in emergency medicine, with clinical documentation burden identified as a central contributing...