Emergency Medicine

Artificial Intelligence in Occlusion-Oriented Digital Reconstruction of Maxillofacial Fractures: Current Applications and Translational Challenges.

Maxillofacial fractures require reconstruction of a functional craniofacial unit rather than isolated realignment of fractured bone. Stable occlusion, mandibular movement, temporomandibular joint position, facial contour, and fixation-device adaptation should be considered as interdependent treatment targets. Digital workflows incorporating CT or CBCT reconstruction, virtual surgical planning, CAD...

"Early Stratification of Risk for Poor Neurological Outcome After Cardiac Arrest Is Improved with Processed EEG Data".

AIM: To evaluate the impact of adding early processed quantitative EEG biomarkers to health record data for early neurological risk stratification after cardiac arrest using machine learning. METHODS: Data available during ICU admission after return of spontaneous circulation (ROSC) were collected from comatose patients, including the processed EEG metrics suppression ratio (SR) and bispectral ind...

Topical exposure to di(2-ethylhexyl) phthalate aggravates atopic dermatitis: an integrated network toxicology, bioinformatics, and experiment analysis.

Di(2-ethylhexyl) phthalate (DEHP) is one of the most widely used plasticizers; however, whether cutaneous DEHP exposure affects atopic dermatitis (AD)...

Clinical Utility of LLM-assisted Chart Review for the Detection of Bleeding Events.

INTRODUCTION: Red blood cell (RBC) transfusions are frequently administered in the intensive care unit (ICU) and are independently associated with inc...

Machine learning models for predicting neonatal bacterial infections: a retrospective cohort study.

Bacterial infections represent a critical threat to neonatal health, accounting for approximately 25% of neonatal mortality globally. Timely and preci...

AI-derived opportunistic screening using chest radiographs identifies age- and sex-associated bone mineral density patterns and supports earlier osteoporosis evaluation.

UNLABELLED: AI-derived opportunistic screening using routine chest radiographs was evaluated in 6,028 adults and internally validated against DXA in a...

Toxicological Knowledge-Guided Graph Learning for Interpretable and Generalizable Molecular Toxicity Prediction.

Early identification of toxic liabilities is essential for improving drug safety and reducing attrition. However, structure-based deep learning models...

Real-World Barriers to and Facilitators of Implementing AI-Based Clinical Decision Support Systems: Scoping Review.

BACKGROUND: Widespread and sustained uptake of AI-based clinical decision support systems (CDSSs) in real-world health care settings is uncommon, desp...

Integrated population-based evidence, network toxicology, single-cell profiling, and in vitro studies elucidate mechanisms connecting PAHs to stroke.

Environmental exposure to polycyclic aromatic hydrocarbons (PAHs) has been associated with cardiovascular disease, yet the specific metabolites and ce...

A large language model-driven multidisciplinary AI agent system predicts delirium in emergency critically ill patients.

Delirium occurs frequently in emergency departments and is associated with poor outcomes and increased burden. Early delirium risk prediction is cruci...

ADRB2 Modulates Asbestos-Induced Pleural Mesothelioma Progression by Influencing IL-17/NF-κB-Related Inflammatory Signalling: An Integrated Network Toxicology, Multi-Omics and Experimental Study.

Pleural mesothelioma (PM) is a highly aggressive asbestos-related malignancy with poor prognosis and limited early diagnostic options. In this study, ...

Evaluating the age of rib fractures through 99mTc-MDP SPECT strategy based on a machine learning algorithm: a preliminary study.

Rib fractures are among the most common injuries in traffic accidents. Accurate evaluation of rib fracture age is important as it assists forensic exp...

Disseminating brief video-based mental health interventions on Instagram: Reach, engagement, and real-world implementation.

OBJECTIVE: Childhood trauma (CT) profoundly impacts mental health. Negative attitudes and stigma surrounding mental health and trauma often deter surv...

Identifying the presence of disc herniations in lumbar spine MRI using Gemini 3.1 Pro.

PURPOSE: Lumbar disc herniation is associated with substantial morbidity, including low back pain, radicular leg pain (sciatica), sensory disturbance,...

Advances in AI's Future in Toxicology: Integrating Computational Prediction and Clinical Translation Through Explainable Artificial Intelligence.

Artificial intelligence (AI) and machine learning are increasingly used in toxicological risk assessment to predict chemical toxicity, identify hazard...

Planning the development of an AI-driven decision support architecture for the recognition of sudden cardiac arrest by 9-1-1 telecommunicators: report of a community engagement and brainstorming meeting.

OBJECTIVES: Sudden cardiac arrest is a leading cause of mortality in Canada (40,000 treatable deaths annually). Despite the benefits of 9-1-1 telecomm...

Short-Term Efficacy of the Artificial Intelligence HeartBot II in Increasing Awareness and Knowledge of Heart Attack in Women: Protocol for a Randomized Controlled Trial With a Waitlist Control.

BACKGROUND: Heart disease remains a leading cause of death for women in the United States. Despite this burden, awareness that heart disease is the le...

Deep-learning triage of three-dimensional pathology datasets for comprehensive and efficient pathologist assessments.

Standard slide-based two-dimensional (2D) histopathology severely undersamples spatially heterogeneous tissue, with each thin 2D section representing ...

Deep learning in Myocarditis: A novel approach to severity assessment.

BACKGROUND: Myocarditis is life-threatening in the acute phase, yet biopsy-the diagnostic gold standard-lacks an objective method to quantify cardiomy...

Hierarchical classification of acute and chronic osteoporotic vertebral compression fractures of the lumbar spine using X-ray images.

OBJECTIVE: To develop and validate a hierarchical deep learning model for differentiating acute and chronic lumbar osteoporotic vertebral compression ...