Identifying and Reporting Dependent Adult abuse

Automated Features, Algorithms, and Technologies of Electronic Early Warning/Track-and-Trigger Systems: Systematic Review.

BACKGROUND: Electronic early warning/track-and-trigger systems (EW/TTS) are crucial for patient monitoring, detecting clinical deterioration (CD), and activating rapid response teams. Understanding the current level of automation in EW/TTS is essential. OBJECTIVE: This study aimed to provide a comprehensive overview and critical assessment of electronic EW/TTS, including automated features, algori...

Nurse-Led Ambient AI Scribe for Patient Safety Incident Investigation Reports (Project NARRATE): Retrospective Pre-Post Comparative Document-Quality Study.

BACKGROUND: Patient safety investigation reports support organizational learning only when they are complete, usable, and sufficiently detailed. Conventional free-text reports are often inconsistent and may omit information needed for review and learning. Project NARRATE (Nursing AI-Refined for Accurate Transcription of Events) is a nursing-led ambient artificial intelligence workflow that uses pr...

Large language models in respiratory care: safety and clinical integration.

BACKGROUND: Large language models (LLMs) are rapidly entering respiratory medicine workflows. Their clinical role remains unclear. A central concern i...

AI echo INSIGHT study: A prospective blinded randomized trial of artificial intelligence echocardiogram interpretation.

BACKGROUND: Transthoracic echocardiography (TTE) is the most commonly performed cardiac imaging modality with over 30 million studies annually. Demand...

ChatGPT and Large Language Models in Contemporary Nursing.

OBJECTIVES: This narrative review synthesizes published evidence on the applications, benefits, limitations and governance considerations of ChatGPT a...

Local recurrence in rectal cancer: from detection to structured reporting.

Despite advances in total mesorectal excision and neoadjuvant therapy, locally recurrent rectal cancer remains a clinically important source of pelvic...

Mortality prediction of road traffic crash with artificial intelligence: a systematic review.

BACKGROUND: Road traffic crashes cause substantial global mortality and disability. Conventional injury severity scores may not fully capture the comp...

Mortality Research With Artificial Intelligence Tools: Applying Language Models to the National Violent Death Reporting System Suicide Narratives, 2003-2023.

Suicide deaths in the United States have increased for a generation with no current evidence of meaningful decline. With advances in data collection a...

Stepwise Diagnostic Evaluation of Chinese Large Language Models: Comparative Study of Common and Rare Diseases.

BACKGROUND: Large language models (LLMs) are increasingly applied in clinical decision support, yet their diagnostic performance in Chinese-language s...

Swimming in the Sea of Real-World Evidence (RWE) Guidance: Why More Guidance Documents Are Needed to Help Researchers Swim.

Real-world evidence (RWE) plays an expanding role in regulatory, health technology assessment (HTA), and lifecycle decision-making, prompting a rapid ...

Barriers, adoption patterns, and determinants of artificial intelligence use among health sciences students in Palestine.

Artificial intelligence (AI) is increasingly integrated into healthcare education worldwide, yet disparities in access, training, and institutional re...

Field readiness of Raman-AI pipelines for microplastic analysis across environmental matrices.

Microplastic monitoring increasingly depends on workflows that can inform decisions beyond controlled laboratory datasets. Raman spectroscopy coupled ...

Accuracy of Artificial Intelligence based chatbots in reporting jaw lesions from multimodal radiographic images: A cross-sectional study.

OBJECTIVES: The current study aimed to quantify the diagnostic accuracy of commonly utilized chatbots including Gemini, Copilot, Claude, and specializ...

Nurse-Led Large Language Model Chatbot for Predicting and Preventing Complications After Coronary Artery Bypass Grafting: Protocol for a Randomized Controlled Trial.

BACKGROUND: Thirty-day unplanned readmission following coronary artery bypass grafting (CABG) affects 10%-20% of patients and is a key quality indicat...

Reporting Quality of Large Language Model Studies: A Cross-Sectional Audit of High-Ranking Radiology and Medical Imaging Journals.

OBJECTIVE: To evaluate adherence to the Minimum Reporting Items for Clear Evaluation of Accuracy Reports of Large Language Models in Healthcare (MI-CL...

Artificial intelligence in breast cancer imaging: a systematic review of diagnostic performance, predictive modeling, and clinical translation.

Artificial intelligence (AI) has rapidly advanced in breast cancer imaging, demonstrating high diagnostic and predictive performance across imaging mo...

Evaluation Methods for Inference-Time Retrieval-Augmented and Graph Retrieval-Augmented Large Language Models in Health Care: Scoping Review.

BACKGROUND: Inference-time retrieval augmentation is increasingly used to improve the traceability and verifiability of large language model (LLM) app...

Mapping the literature on improving primary-to-secondary care referrals through the lens of the Quintuple Aim framework for healthcare improvement: a scoping review.

OBJECTIVES: To explore and map the literature on referral pathway gaps and improvement strategies in primary healthcare (PHC) to secondary healthcare ...

Performance of federated learning models in health services research: A systematic review and meta-analysis.

PURPOSE: This study aimed to assess the performance of federated learning (FL) models and compare their performance with local and centralized models....

Reporting of race and ethnicity in studies of artificial intelligence in pediatric urology A secondary analysis of the AI-PEDURO online repository.

INTRODUCTION: While an increasing number of artificial intelligence (AI) models are being developed in pediatric urology, the extent of race/ethnicity...