Domestic Violence

Living evidence and gap maps: a scoping review of automation and living mode parameters reported in 44 digital interfaces and their documentation.

OBJECTIVE: To examine how continually updated, living evidence and gap maps (L-EGMs) with an online presence report planned update schedules, retirement plans, living status, use of automation across review stages, and the methodological guidance cited to support their conduct and reporting. STUDY DESIGN AND SETTING: A cross-sectoral scoping review of digital L-EGM interfaces, which act as foundat...

Transparent reporting is central to reproducible radiological AI research: A call to action.

BACKGROUND: Artificial intelligence (AI) is increasingly embedded in radiology research and practice, yet concerns about the reproducibility of AI studies remain a key barrier to regulatory acceptance and clinical translation. Transparent reporting across the analytic pipeline is essential for independent verification, evidence synthesis, and safe implementation. PURPOSE: To examine major barriers...

Artificial intelligence innovations in substance use prevention on social media: A scoping review.

OBJECTIVES: This scoping review examined the current application of artificial intelligence (AI)/machine learning (ML) models on social media platform...

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...

Assessing the clinical competence of large language models for tobacco use disorder: A multi-domain expert evaluation.

BACKGROUND: Tobacco use disorder (TUD) remains the leading preventable cause of death globally, yet fewer than one-third of users receive guideline-co...

Artificial intelligence for venous thromboembolism risk stratification in surgical patients: a systematic review.

Venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE), is a significant complication in surgical patients. Ar...

Improving Evidence-Based Practice Through the Development and Validation of Key Wo\rds to Identify Intervention Articles in Communication Disorders.

PURPOSE: Although evidence-based practice (EBP) promotes better clinical practice, implementing it in speech-language pathology is challenging. A limi...

Evaluating Artificial Intelligence-Generated Nursing Care Plans: A Scenario-Based Comparative Study of Accuracy, Completeness, Quality, and Readability.

AIM: This study aimed to evaluate the ability of three generative artificial intelligence tools (ChatGPT, Gemini and DeepSeek) to generate clinically ...

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...

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...

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...

Natural Language Processing and Machine Learning Classification Model for Injury Mechanism in Trauma.

INTRODUCTION: Creating and maintaining research databases in trauma can be resource intensive. Natural language processing (NLP) may assist by extract...

Artificial Intelligence in Mammography Screening: A Narrative Review of Progress, Pitfalls, and Potential.

Artificial intelligence (AI), particularly deep learning (DL), is transforming the field of medical imaging and holds substantial promise for advancin...

Machine learning to risk stratify individuals for undiagnosed atrial fibrillation at scale using population-wide electronic health records.

AIMS: Electronic health records (EHR) can be used to target atrial fibrillation (AF) screening. We evaluated the performance of risk prediction models...

Digital breast tomosynthesis and reading with artificial intelligence.

Digital breast tomosynthesis (DBT) increases sensitivity and specificity compared to digital mammography (DM) in the early detection of breast cancer....

Contribution of social determinants to symptoms of generalized anxiety disorder.

Symptoms of anxiety are known to be triggered by a range of life context factors including early life trauma, poor sleep quality, infrequent exercise,...

Exploring the impact of reimbursement ratios on willingness to vaccinate: A mixed-effects modeling approach using panel data.

Vaccination remains one of the most cost-effective methods for disease prevention. However, utilization of self-paid vaccines, including EV71, varicel...

AI-based BRAIx risk score for the intermediate-term prediction of breast cancer: a population cohort study.

BACKGROUND: Artificial intelligence (AI)-based algorithms are being implemented in breast screening to detect breast cancers on mammographic images. W...

Patterns of AI Use in Clinical Work by Hospitalists: Survey Study.

BACKGROUND: Artificial intelligence (AI) tools are widely and freely available for clinical use. Understanding hospitalists' real-world adoption patte...

In-Hospital Mortality Prediction of Patients Requiring Extracorporeal Membrane Oxygenation Using Composite Lactate Metrics and Weight of Evidence Modeling.

BACKGROUND: Mortality prognostication in adult patients requiring extracorporeal membrane oxygenation (ECMO) is not accurate or established. We hypoth...