Emergency Medicine

Application of machine learning in osteoporosis screening: a narrative review.

Machine learning has the potential to address limitations of traditional osteoporosis screening through advanced data processing and pattern recognition capabilities. This review provides a critical analysis of ML applications in opportunistic screening, precision risk assessment, and quantitative bone quality analysis, while addressing current implementation challenges and future research directi...

Integrated machine learning and experimental validation reveal S6K2 as a key target of 6PPD-quinone in bladder cancer.

Tire and Road Wear Particles (TRWP) are pervasive environmental contaminants, yet the molecular mechanisms linking their toxic derivative, 6PPD-quinone (6PPD-Q), to bladder cancer (BLCA) progression remain obscure. This study integrates network toxicology with experimental validation to elucidate this complex pathogenicity. We screened six representative TRWP compounds and utilized a comprehensive...

Exploring the mechanisms of diethyl phthalate-induced diabetic nephropathy through integrated network toxicology, machine learning, and experimental validation.

Phthalate plasticizers, especially diethyl phthalate (DEP), are linked to metabolic disorders, while their precise role and mechanism in diabetic neph...

Embedded AI-Assisted Otoscopic Image Screening for Pediatric Otitis Media.

OBJECTIVE: To evaluate an embedded artificial intelligence (AI) system for otoscopic image-based screening and prediagnostic triage of pediatric otiti...

Risk factors and a predictive model for steinstrasse formation after shock wave lithotripsy in pediatric urolithiasis.

A machine-learning-based tool for stroke risk prediction in blunt cerebrovascular injury: development and preliminary evaluation.

PURPOSE: Stroke risk correlates with the Biffl grading system in blunt cerebrovascular injury (BCVI). Although anti-thrombotic therapy is the mainstay...

Extended Rice-Thomson analysis and atomistic simulations revealing grain boundary effects on fracture in refractory high-entropy alloys.

Understanding how grain boundaries mediate fracture remains a critical challenge in designing ductile, high-performance refractory alloys. Here, we ex...

Utility of Machine Learning in Predicting Catastrophic Cardiac Complications Following Hip and Knee Periprosthetic Fracture Surgery Using Preoperative Parameters.

BACKGROUND: With the rising prevalence of primary total hip (THA) and knee arthroplasties (TKA), the number of periprosthetic fractures (PPF) is expec...

RadTranslateGPT: An Improved AI-Based System for Translation and Simplification of Structured Radiology Reports.

INTRODUCTION: Radiology reports often contain complex medical jargon that can be difficult for patients to understand, especially those with limited E...

Thrombosis after surgical splenectomy - why, in whom and can we prevent it?

Splenectomy remains a common operation performed in the setting of trauma, haematological disease, malignancy and diagnostic purposes. Contemporary ev...

Can an artificial intelligence electrocardiogram algorithm improve diagnostic accuracy for acute coronary occlusion in the difficult subset of canceled catheterization lab activations?

BACKGROUND: ST-segment elevation myocardial infarction (STEMI) and its equivalents describe the electrocardiogram (ECG) findings of acute coronary occ...

Investigating the potential risk of nicotine exposure on glioblastoma: Integrating Mendelian randomization and network toxicology analysis.

OBJECTIVE: To investigate the potential risk of nicotine exposure on glioblastoma multiforme (GBM). METHODS: A two-sample Mendelian randomization (MR)...

Application of Telehealth and Artificial Intelligence in Military Health Care: A Promising Combination for the Future.

BACKGROUND: Military and peace-support operations increasingly depend on medical capability delivered under difficult circumstances: distance, limited...

Leveraging Large Language Models for Contextual Prioritization of Contaminants of Emerging Concern in Chemical Mixtures.

Effective management of chemical mixtures presents a continuing challenge due to the growing diversity and inadequate characterization of contaminants...

Impact of Chemical Quality on High-Throughput in Vitro Assays: A Tox21 Study.

The Tox21 10K chemical library, an in vitro toxicology toolbox consisting of more than 8900 unique chemical entities including environmental chemicals...

Development and validation of a prediction model for respiratory complications and in-hospital mortality in trauma patients.

Opportunistic Cardiovascular Risk Assessment Using Routine Head CT in the Emergency Department.

BACKGROUND: Routine noncardiac computed tomography (CT) imaging may contain information about cardiovascular risk. Head computed tomography (CTH) is a...

Establishing generalizability of wearable-enabled blood volume decompensation status estimation algorithms using transfer learning.

Timely assessment of blood volume decompensation status (BVDS) is essential for effective trauma intervention, especially in prehospital and resource-...

Hybrid experimental-QSAR-artificial intelligence framework for chronic ecological risk assessment of emerging pollutants in coastal environments.

Urbanized coastal zones are increasingly exposed to complex mixtures of pharmaceuticals and illicit drug markers (PhACs), yet ecological risk assessme...

Artificial intelligence in emergency nursing: A scoping review of applications and implications.

INTRODUCTION: Artificial intelligence (AI) has advanced rapidly in healthcare; however, its application in emergency nursing remains underexplored. Th...