Clinical Trials

Impact of Availability of Computer-Aided Detection Devices on Adenoma Detection During Colonoscopy: A Cluster Randomized Study.

BACKGROUND AND AIMS: Endoscopists' colonoscopy adenoma detection rates (ADR) are inversely associated with their patients' risk of post-colonoscopy colorectal cancer death. Though randomized controlled trials have demonstrated that computer-aided detection (CADe) devices significantly improve ADR, real-world studies have generally failed to demonstrate benefit. METHODS: In this pragmatic quality i...

Automated Assessment of PPE Compliance with Fast Lightweight Deep Learning Based Computer Vision.

UNLABELLED: This study presents a fast, lightweight computer vision framework that achieves high accuracy in verifying the correct use of goggles and N95 masks. For ergonomics practitioners, this model offers a computer vision tool for enhancing workplace safety compliance, that operates up to five times faster than benchmark models. The proposed algorithm enables automated PPE compliance checks a...

Use of artificial intelligence in magnetic resonance imaging across the epileptic patient's journey: A meta-analysis of four clinical applications.

OBJECTIVE: The application of artificial intelligence/machine learning (AI/ML) to magnetic resonance imaging (MRI) promises to enhance and support cli...

Infant Brain Age Estimation With T1w/T2w Ratio MRI: A Myelination-Aware Deep Learning Approach.

BACKGROUND: Brain age estimation provides a noninvasive MRI biomarker of neurodevelopment. In infancy, rapid regionally ordered myelination reflects b...

Performance Evaluation of GPT-5, Grok 4, and DeepSeek R1 in Interpreting Complete Blood Count Reports for Hematologic Diseases: Retrospective Comparative Study.

BACKGROUND: Large language models (LLMs) demonstrate potential in the laboratory, yet rigorous clinical evaluation remains limited. The opacity of LLM...

Using the Machine Learning Algorithm XGBoost to Understand the Correlates of Wearing Hearing Protection in Central States' Agricultural Producers.

PURPOSE: Hearing loss is a common work-related condition. Estimates suggest that 46%-86% of agricultural workers have hearing loss. Agricultural safet...

AI-Assisted Video Monitoring for Tracheostomy-Dependent Infants: A Proof-Of-Concept Study.

OBJECTIVE: To retrospectively evaluate Eyes-On, a patient-personalized AI-assisted video analysis system for frame-level detection of tracheostomy tub...

A MOOC-based and high-fidelity surgical simulation-integrated clinical internship mode in optometry teaching for ophthalmology graduate students.

BACKGROUND: Clinical medicine postgraduates are expected to attain competencies equivalent to senior resident physicians. However, ophthalmology gradu...

Pharmaceutical-inspired insecticide discovery: Artificial intelligence, chemoinformatics, and target-based design for next-generation insect control.

This review examines how pharmaceutical-inspired discovery logic can help revitalize insecticide innovation by integrating target-based design, chemoi...

Mediating effects of artificial intelligence readiness and self-efficacy on innovative behavior in Chinese standardized training nurses: a structural equation model study.

BACKGROUND: Innovative behavior is crucial for enhancing clinical efficiency, promoting patient recovery, and advancing the nursing discipline. As an ...

Physical Attractiveness and Chances of Being Invited to Interview With a Medical Residency Program: Retrospective Cohort Study.

BACKGROUND: Applicants participating in the Residency Match generally submit a photograph through the Electronic Residency Application Service (ERAS)....

Early Immunological Biomarkers for Personalized Treatment Selection in Severe COVID-19: Post Hoc Machine Learning Analysis of a Randomized Clinical Trial.

BACKGROUND: Severe COVID-19 is a global health concern despite continuous vaccination campaigns because current therapies, such as dexamethasone and r...

How Following Medical Artificial Intelligence Advice Can Mitigate Malpractice Liability: Cross-National Insights from a Randomized Trial.

Artificial intelligence (AI) increasingly influences clinical decision-making, yet its recommendations may diverge from standard care. Although malpra...

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...

Tuberculosis in households with infectious cases in Kampala city: Harnessing health data science for new insights on an ancient disease with persistent, unresolved problems.

Tuberculosis (TB) is prevalent in Uganda and overlaps with a high rate of HIV/TB coinfection. While nearly all hospital-based TB cases in Kampala, the...

Development and validation of a machine learning-based clinical decision support tool for stratifying intravenous medication risk in hospitalized patients with heart failure.

INTRODUCTION: Hospitalized patients with heart failure (HF) frequently receive multiple high-risk intravenous (IV) medications, placing them at a subs...

Evaluation of large language models in terms of safety, contraindications, and adverse effect information related to botulinum toxin applications.

BACKGROUND: Large language models (LLMs) are increasingly used for the dissemination of health-related information. However, data regarding the accura...

Immersive virtual reality for cognitive rehabilitation in patients who had a stroke: study protocol for a randomised controlled trial.

INTRODUCTION: Poststroke cognitive impairment (PSCI) is a prevalent complication of stroke, characterised by deficits in one or more cognitive domains...

Training effect of a deep learning-based blended teaching model on ECMO transport for ICU nurses: a prospective, parallel-group, randomized controlled trial.

OBJECTIVE: Given the high alignment between deep learning and blended teaching objectives, blended teaching provides a feasible pathway for achieving ...

The relationship between AI self-efficacy and critical thinking among nursing students: A network analysis.

AIM: This study used network analysis to characterize the internal structure of artificial intelligence self-efficacy (AISE) among nursing students an...