Emergency Medicine

External validation of an AI-Based fracture detection tool for hip and pelvic radiographs in a multicenter retrospective cohort.

OBJECTIVE: Artificial intelligence tools show promise in fracture detection but may be impaired by hidden stratification. We aim to evaluate the diagnostic accuracy of a commercially available AI tool for detecting hip and pelvic fractures, with emphasis on clinically relevant subgroups and AO/OTA fracture classifications. MATERIALS AND METHODS: This retrospective multicenter diagnostic test accur...

Deviation From AI-Predicted Implant Sizes in Total Hip Arthroplasty Is Associated With Increased Complication Risk.

BACKGROUND: Patient characteristics may predict implant sizes in total hip arthroplasty (THA), but the clinical value and generalizability of such models remain uncertain. This study evaluated the accuracy and relevance of an artificial intelligence (AI)-driven prediction tool for THA sizing in a diverse population. METHODS: We retrospectively reviewed 2410 primary THAs at 2 academic hospitals (20...

Network toxicology integrated with machine learning and SHAP analysis identifies overlapping immune signatures between Di(2-ethylhexyl) phthalate (DEHP) and Sjögren's syndrome.

Accuracy of GPT-5 and GPT-4o in diagnosing STEMI from 12-Lead ECGs: A comparative study with cardiologists and emergency physicians.

BACKGROUND: ST-segment elevation myocardial infarction (STEMI) requires rapid, accurate electrocardiogram (ECG) interpretation. The diagnostic effecti...

6PPD-quinone promotes ovarian cancer progression: Insights from network toxicology, machine learning, and in vitro validation.

6PPD-quinone (6PPD-Q), a toxic tire-derived antioxidant transformation product, is a pervasive environmental contaminant linked to reproductive toxici...

Evaluating Generative Artificial Intelligence Models' Responses to Questions About Scaphoid Fracture and Scaphoid Nonunion.

PURPOSE: To evaluate and compare the responses of ChatGPT and Google Gemini to common patient questions about scaphoid fracture and scaphoid nonunion,...

Triage Nurses' Perceptions of Artificial Intelligence: A Cross-Sectional Study.

INTRODUCTION: Emergency department crowding and increasing patient complexity challenge traditional triage models. Artificial intelligence may support...

Rejoining fragmented ancient bamboo slips with physics-driven deep learning.

Bamboo slips are a crucial medium for recording ancient civilizations in East Asia. However, many excavated bamboo slips have been fragmented into tho...

PM2.5 exposure induces functional alterations in pregnant rats heart and in human stem cell derived cardiac spheroids.

Air pollution is a major cardiovascular risk factor, with particulate matter (PM) posing significant threats. The Po Valley remains among Europe's mos...

Adverse outcome pathway-informed machine learning for predicting vascular toxicity of emerging organic pollutants.

Emerging organic pollutants (EOPs) are increasingly detected in wastewater and pose potential vascular toxicity risks that remain inadequately assesse...

AI-guided surgical decision support system for corneal laceration repair: a prospective, non-randomized controlled feasibility study.

To evaluate the feasibility and application value of a transfer learning-based artificial intelligence (AI) system for wound recognition and suture po...

Multidisciplinary Optimization Design of pVADs Using Analytical Target Cascading-Guided Genetic Algorithm.

PURPOSE: The purpose of this article is to address the limitations of inconsistency between the impeller and motor when designing Percutaneous ventric...

Percutaneous nephrostomy guidance by a convolutional-neural-network-based optical coherence tomography endoscope.

Percutaneous nephrostomy is widely used in kidney access surgeries. Despite its prevalence in urological interventions, it presents two operational ch...

Phenotypic clustering of myocardial infarction complicated by out-of-hospital cardiac arrest using unsupervised machine learning.

BACKGROUND: Patients with myocardial infarction (MI) complicated by out-of-hospital cardiac arrest (OHCA) represent a heterogeneous population with va...

Deep Learning-Based ROSC Prediction and ECG Phenotyping in Out-of-Hospital Cardiac Arrest.

INTRODUCTION: Electrocardiogram (ECG) signals during cardiac arrest contain detailed information on cardiac rhythm characteristics and have been assoc...

Unraveling the connection between PFOA and bladder cancer: A study integrating network toxicology, molecular docking, and experimental validation.

PFOA, an environmental pollutant linked to bladder cancer, has unclear molecular mechanisms. Integrating transcriptomic data with network toxicology a...

Early Prediction of Standing at Discharge in Moderate-to-Severe TBI: A Clinical Machine Learning Model Integrating Modifiable and Nonmodifiable Factors.

OBJECTIVE: To develop and internally validate a machine learning model to predict favorable standing ability at hospital discharge in patients with mo...

Screening of Respiratory Toxicity of Environmental Compounds Based on Multimodal Feature Fusion Model.

The respiratory system constitutes the primary interface between the human body and the external environment, demonstrating particular vulnerability t...

Machine Learning-Enhanced Feature Engineering for High-Fidelity Quasi-Isentropic Waveform Prediction under Data Sparsity Constraints.

The quasi-isentropic loading method based on multidimensional gradient structures plays a critical role in acquiring dynamic physical parameters and s...

Field Foresight-Predicting the Need for Massive Transfusion, ICU Utilization, and Mechanical Ventilation for Traumatically Injured Patients.

INTRODUCTION: Expeditiously predicting outcomes is essential to allocating blood and intensive care resources. We hypothesize the use of external inju...