Emergency Medicine

Integrated multi-omics and experimental validation reveal CSK and FBLN1 as key targets of stanozolol in accelerating atherosclerosis.

BACKGROUND: Stanozolol, a synthetic anabolic androgenic steroid (AAS) widely abused to enhance performance, has poorly defined toxicological mechanisms in atherosclerosis (AS). METHODS: An AS model was established in ApoE-/- mice, followed by a 12-week stanozolol intervention. Effects on lipid metabolism, systemic inflammation, and plaque formation were assessed. Potential targets were predicted v...

Predictive modeling of urinary 8-hydroxy-2´-deoxyguanosine (8-OHdG) in metal workers: A comparative study of machine learning algorithms in toxicology.

Urinary 8-hydroxy-2´-deoxyguanosine (8-OHdG), a biomarker for oxidative DNA damage, is commonly used to assess the repair of reactive oxygen species (ROS) induced DNA damage. This study developed predictive models to quantify 8-OHdG concentrations in urine samples based on demographic and exposure-related variables from metal workers (21.27 ng/ml) and controls (12.63 ng/ml) using ELISA and machine...

Development of a deep learning based framework for classification of Indian venomous snakes integrated with explainable artificial intelligence for primary and emergency care providers.

BACKGROUND: Snakebite envenoming is a significant global health crisis that has been long neglected as a global health priority. It is a huge problem ...

Development, internal testing, and external validation of an interpretable machine-learning model for predicting imaging-confirmed in-hospital postoperative deep vein thrombosis in older patients with patellar fractures.

BACKGROUND: Older patients with patellar fractures may be at increased risk of postoperative deep vein thrombosis (DVT) because of trauma, perioperati...

Prediction of delirium in trauma patients using interpretable machine learning.

This study aimed to identify key risk factors for delirium in trauma patients and to develop an interpretable machine learning model using routinely a...

TASC: a time-aware sequence clustering framework with uncertainty quantification for electronic health record trajectories.

Longitudinal electronic health record (EHR) trajectories are highly heterogeneous, sparse, and irregular, making unsupervised temporal pattern discove...

EXPRESS: Detection of Fentanyl Analogues in Illicit Drug Samples Using Surface-Enhanced Raman Spectroscopy and Random Forest Classification.

The ongoing overdose crisis is largely fueled by unregulated opioids; therefore, harm reduction measures like drug checking are forced to adapt to the...

Navigating PI-RADS v2.1 in clinical practice: pitfalls, variability, and the supportive role of AI.

Prostate Imaging Reporting and Data System (PI-RADS) version 2.1 has substantially advanced the standardization of prostate MRI acquisition, interpret...

Large Language Models Exhibit High Performance as Computable Phenotypes for Pediatric Asthma Exacerbation Detection in a Retrospective, Observational Study of Emergency Medical Services Encounters.

OBJECTIVES: Pediatric asthma exacerbations are a common emergent condition treated by prehospital emergency medical services (EMS). However, retrospec...

DEHP-induced male reproductive toxicity: Evidence from population studies, animal experiments, and multi-omics profiling.

OBJECTIVE: To evaluate the association between di(2-ethylhexyl) phthalate (DEHP) exposure and testosterone deficiency in adult men, and to explore mol...

Rural Airborne PM2.5-bound Microplastics and Heavy Metals: GIS-AI Risk Assessment Review.

Fine particulate matter (PM2.5) is a critical air pollutant and carrier of toxic co-contaminants, including microplastics (MPs) and heavy metals (HMs)...

Towards a clinically integrated artificial intelligence tool for triage of skin cancer.

Skin cancer is one of the most prevalent malignancies worldwide, with early detection critical to improving outcomes. However, in low-resource setting...

Substance-induced manic psychosis in which delusions were corroborated by a chatbot - case report.

BACKGROUND: This case describes a substance-induced manic episode with psychotic features in which interaction with an AI (artificial intelligence) ch...

CT-based deep learning radiogenomics for predicting key glioma genotypes (IDH, ATRX, EGFR, TP53).

PURPOSE: Molecular subtyping guides diagnosis and targeted therapy for gliomas. Although MRI-the current imaging standard-can be time-consuming and is...

Performance and safety of a fine-tuned small language model for pediatric emergency triage: A benchmark study.

Pediatric emergency triage is a safety-critical task, and recent studies have explored whether artificial intelligence, including language models, can...

Deep learning-based arterial waveform analysis for predicting postoperative cerebrovascular events in pediatric patients with Moyamoya disease.

BACKGROUND: Postoperative cerebrovascular events, including transient ischemic attacks, infarctions, and hemorrhages, remain a significant concern in ...

Integrative Network Toxicology and Machine Learning Identify AKR1C3 as a Candidate Functional Target of Cypermethrin in Colorectal Cancer.

The potential contribution of foodborne pesticide residues to colorectal cancer (CRC) remains insufficiently understood. In this study, we integrated ...

Leveraging Artificial Intelligence in Allergy, Asthma, and Immunology With Environmental Exposures.

Artificial intelligence (AI) in environmental health science is revolutionizing data analysis and problem-solving approaches. These technologies facil...

Autonomous Uncertainty Quantification for Computational Point-of-Care Sensors.

Computational point-of-care (POC) sensors enable rapid, low-cost, and accessible diagnostics in emergency, remote, and resource-limited areas that lac...

Agreement between three state-of-the-art deep learning bone age estimation models and chronological age in a large contemporary pediatric cohort.

BACKGROUND: Radiographic bone age estimation is routinely performed in children to evaluate short stature, early or late puberty, and endocrine disord...