Emergency Medicine

Development and external validation of a machine learning model for predicting tigecycline-associated drug-induced liver injury.

Tigecycline (TGC) is widely used to treat severe multidrug-resistant infections but can cause drug-induced liver injury. Existing prediction studies frequently lack external validation and offer limited clinical interpretability. We performed a multicenter retrospective cohort study of 1,946 adult inpatients who received TGC at three tertiary hospitals in Jiangsu, China. Liver injury was defined b...

Artificial Intelligence-Assisted Triage in Emergency Departments: A Scoping Review of Clinical Applications, Outcomes, and Implementation Challenges.

OBJECTIVE: Emergency department (ED) triage determines patient prioritization, early risk recognition, and allocation of limited resources. Artificial intelligence (AI) has been explored to support triagerelated decision-making, but the evidence remains heterogeneous. This scoping review aimed to map applications of AI-assisted triage in EDs and summarize reported outcomes, safety, equity, and imp...

Pilot Evaluation of a Novel Artificial Intelligence (AI) Heart Rate Variability (HRV)-Guided Risk Stratification for Chest Pain in the Emergency Department: A Randomized Controlled Trial.

BACKGROUND: Heart rate variability (HRV) analysis powered by artificial intelligence (AI) offers a rapid, non-invasive, and objective approach for acu...

Comparative Assessment of Performance of Domain-Specific and Primed Versus Non-Primed Artificial Intelligence Chatbots for Clinical Decision-Making in Injuries to the Primary Dentition: An Exploratory Pilot Study.

BACKGROUND/AIMS: To compare the performance of a domain-specific dental trauma chatbot with general-purpose artificial intelligence chatbots under pri...

Deep-Learning-Driven High-Fidelity In Vivo Hyperspectral Fluorescence Imaging Under Extreme Photon-Limited Conditions.

In vivo hyperspectral fluorescence imaging (fHSI) has transformed biomedical research by enabling qualitative/quantitative analysis of multiplexed mol...

Artificial Intelligence in Spiritual Care: Modified Delphi Study.

BACKGROUND: Spiritual care providers are increasingly challenged to address the introduction of AI within the ethical, theological, and organizational...

Molecular mechanism of lead exposure induced atrial fibrillation: A systematic study based on network toxicology, machine learning, and in vivo and in vitro experiments.

Lead is a ubiquitous environmental toxic metal. Lead exposure is closely linked to an increased risk of atrial fibrillation (AF), yet its molecular me...

Mechanics, Fracture, and Fragmentation of Thrombi: A Computational Study Review.

Thrombosis drives myocardial infarction, acute ischemic stroke and pulmonary embolism, yet more than half of patients undergoing mechanical thrombecto...

Emerging Technologies in Oncology Nursing: Integrating Informatics Competencies to Advance Safe, High-Quality, and Compassionate Care.

AIM: To describe the rapid evolution of emerging digital technologies in oncology nursing and clarify the essential informatics competencies required ...

miR-124 Ameliorates Spatial Memory Deficits in Rats Exposed to Single-Prolonged Stress by Downregulating IQGAP1 to Regulate Actin-Binding Proteins and Apoptosis in Hippocampal Neurons.

Post-traumatic stress disorder (PTSD) is a highly prevalent, trauma-induced psychiatric condition characterized by persistent cognitive-affective dysf...

Police emergency dispatch model based on emergency level analysis and traffic planning.

Emergency dispatching and rescue during emergencies have become a hot research topic in the field of transportation planning. Therefore, to address th...

Unveiling the Structural Determinants of PFAS Toxicity: A Graph Neural Network and Interpretability Analysis.

The rapid proliferation of per- and polyfluoroalkyl substances (PFASs) necessitates high-throughput tools to assess safety and prevent regrettable sub...

Bigger Is Not Always Better: Computational Efficiency in Lexical Prehospital Triage Modeling.

INTRODUCTION: In future large-scale combat operations, military medics will likely face staggering numbers of casualties in the face of resource const...

[Systems saving lives: a systems-based approach to cardiac arrest management].

Out-of-hospital cardiac arrest remains a major public health challenge worldwide, with survival largely determined by the timeliness, quality, and org...

Time Is Aorta: Can Artificial Intelligence Improve Surgical Timelines in Acute Type A Aortic Dissection? A Comprehensive Review.

BACKGROUND AND AIMS: Acute Type A aortic dissection (ATAAD) is a surgical emergency in which delays in diagnosis, transfer, and operative activation i...

Diagnostic Ambiguity in Appendicitis: Comparing Failure Modes of Large Language Models and Surgeons.

BackgroundSuspected acute appendicitis is difficult to triage in atypical presentations, including pediatric and geriatric cases and scenarios with mu...

DINCH Exposure Contributes to Osteoarthritis Pathogenesis via TSPO-Mediated Chondrotoxicity: Evidence from In Silico Prediction to Experimental Validation.

Diisononyl cyclohexane-1,2-dicarboxylate (DINCH), a widely used plasticizer substitute, has been widely detected in human populations and has emerged ...

Improving Follow-Up of Incidental Pulmonary Nodules in the Emergency Department Using an Artificial Intelligence-Supported Workflow.

BACKGROUND: Incidental pulmonary nodules (IPNs) are frequently identified on computed tomography (CT) scans but are often associated with poor rates o...

Measures matter: assessing childhood maltreatment and emotion dysregulation in a transdiagnostic sample.

Background: Childhood maltreatment (CM) is a major risk factor for different mental disorders and transdiagnostic mechanisms, including emotion dysreg...

Semantic knowledge improves molecular machine learning for chemical toxicity prediction.

Quantitative structure-activity relationship (QSAR) modeling predicts chemical activity from structural and physico-chemical molecular properties. Bey...