Surveys

Cardiovascular risks of plastic-associated chemicals: Integrating mixture modeling and SHAP-explained machine learning to unravel linear and non-linear associations.

INTRODUCTION: Plastic-associated chemicals (PACs) are widely detected environmental contaminants, yet their cardiovascular relevance in the context of concurrent exposure remains unclear. We evaluated individual and mixture-level associations of urinary PAC biomarkers with cardiovascular disease (CVD) status among U.S. adults. METHODS: We analyzed 3,831 adults from the National Health and Nutritio...

Causal treatment effects of gait-analysis-informed surgery on the Gait Outcomes Assessment List in children with cerebral palsy.

AIM: To estimate the effect of surgery on parent-reported gait outcomes as measured using the Gait Outcomes Assessment List (GOAL) questionnaire in a cohort undergoing surgery guided by instrumented gait analysis. METHOD: This was an observational study (n = 146 individuals, 59 females [40%], median age 7 years 10 months [interquartile range 6 years to 10 years 10 months]) classified in Gross Moto...

Development of a scale for measuring the perception of artificial intelligence among mental health consumers.

BACKGROUND: Artificial Intelligence (AI) has emerged as a transformative force revolutionizing various sectors, including healthcare, particularly the...

Predicting medication non-adherence using machine learning: Incorporating Complementary and Alternative Medicine (CAM) beliefs in Malaysian chronic disease patients.

Medication non-adherence among chronic disease patients remains a major contributor to poor health outcomes and medication wastage, particularly in mu...

Do Large Language Models Support Nursing Care Planning? A Scoping Review of Applications, Evaluation Approaches and Outcomes.

AIM: To examine the overall performance of large language models (LLMs) in generating nursing care plans, clarify their role in nursing practice and i...

The use of artificial intelligence to predict postoperative outcomes following percutaneous nephrolithotomy: A systematic review of prognostic modeling studies.

Artificial intelligence (AI) is increasingly applied in clinical practice to enhance prediction of postoperative outcomes. This systematic review eval...

Use of heart rate variability in prediction of clinical deterioration in critically ill hospitalised adults: a systematic review protocol.

INTRODUCTION: Heart rate variability (HRV) is a measurement derived from the beat-to-beat variation in heart rate and reflects the complex interaction...

Reliability-Aware View-Adaptive Consensus for 3D Cephalometric Landmark Identification.

Cone-beam computed tomography (CBCT)-based three-dimensional (3D) cephalometric analysis relies on accurate anatomical landmark identification, yet ma...

A comparative analysis of readability, quality, and reliability in large language model outputs pertaining to knee osteoarthritis queries.

This study aims to comparatively examine the readability, accuracy, and quality of responses provided by artificial intelligence (AI)-based chatbots s...

Saudi Medical Students' Perceptions and Attitudes of Integrating Generative Artificial Intelligence Integration in Medical Education: A Cross-Sectional Study.

BACKGROUND AND AIMS: Generative Artificial Intelligence (GenAI) has catalyzed a transformation in medical education. Understanding learners' perceptio...

Preliminary Evaluation of a Dental Virtual Standardized Patient in Endodontic Clinical Reasoning and Decision-Making: Face and Construct Validity.

AIM: To develop and evaluate a dental virtual standardized patient (D-VSP) integrating natural-language intent recognition, a high-fidelity haptic sim...

Turkish Validity and Reliability Study of the Fear of Artificial Intelligence Scale Among Nursing Students.

Background and Purpose: Artificial intelligence (AI) is increasingly used in nursing education and clinical practice. Fear of AI among nursing student...

Mapping the evidence on artificial intelligence-based clinical decision support systems for undergraduate nursing students: a scoping review protocol.

OBJECTIVE: This scoping review will map the scope and nature of the available evidence on the use of artificial intelligence-based clinical decision s...

A Multidimensional Digital Health Platform to Support Intrinsic Capacity and Healthy Aging: Pilot Feasibility Study.

BACKGROUND: By 2050, 22% of the global population will be aged 60 years or older, with Europe experiencing rapid aging. This increase in chronic disea...

Comparative Evaluation of AI Chatbots for Testicular Cancer Education: Validity, Information Quality, and Readability.

BACKGROUND: Large language models (LLMs) are increasingly used in health information seeking, but their performance in testicular cancer education rem...

Mapping the Reliability-Readability Gap in the Education of Patients With Age-Related Macular Degeneration Across 6 Large Language Models: Comparative Evaluation Study.

BACKGROUND: Artificial intelligence-generated health information is increasingly used by patients, but its reliability, visible transparency indicator...

Development and Evaluation of Individualized Music Therapy for Common Mental Disorders: Protocol for a Multistage Study.

BACKGROUND: Pharmacotherapy for common mental disorders is frequently limited by adverse events and suboptimal adherence. While music therapy offers a...

Large Language Models in German Continuing Medical Education Assessments: Protocol for a Fully Crossed Experimental Study.

BACKGROUND: Continuing medical education (CME) is a legal and ethical obligation for physicians in Germany. The rapid rise of large language models (L...

Enhancing trust and decision-making in AI-driven construction: Applying cognitive fit theory to interface clarity and alignment.

As artificial intelligence (AI) systems increasingly support decision-making in the construction sector, understanding the cognitive mechanisms behind...

High Resolution Isotropic 'Pseudo' 3D Cine imaging with Automated Segmentation using Concatenated 2D Real-time Imaging and Deep Learning.

BACKGROUND: Conventional cardiovascular magnetic resonance (CMR) in pediatric and congenital heart disease uses 2D, breath-hold (BH), balanced steady ...