Surveys

Bridging Machine Learning and Event-Based Analyses to Assess Maternal Contingent Responses to Infant Nondistress and Distress Vocalizations From Home Audio Recordings.

Caregiver-infant vocal interactions are foundational for early development, yet most evidence is derived from brief laboratory or home-visit observations and assessing caregiver-infant vocal contingency in everyday settings requires scalable methods. To this end, we integrated machine learning (ML) with traditional event-based analyses to measure maternal contingent vocal responsiveness assessed f...

Large Language Models as Clinical Support Tools in Drug Information Services: Performance Comparison With Pharmacists.

BACKGROUND: Large language models (LLMs) are increasingly explored for drug information support, yet their reliability and clinical applicability remain uncertain. This study evaluated multiple LLMs in responding to real-world drug information questions retrieved from a university hospital in Thailand, focusing on clarity in Thai, concordance with pharmacist responses, relevance, context awareness...

Trusting the Algorithm or Trusting the Nurse? Critical Care Nurses' Experiences of Automation Bias and Professional Autonomy in AI-Assisted Early Warning.

BACKGROUND: Artificial intelligence-assisted early warning systems (AI-EWS) are increasingly integrated into critical care, yet little is known about ...

Comparative performance of large language models for appraising bias in real-world evidence studies.

BACKGROUND: Real-world evidence (RWE) is increasingly used to inform regulatory and payer policy decisions and health technology assessment, yet appra...

Artificial intelligence in prior authorization and coverage decisions: A systematic review of methods, evidence gaps, and future implications for patient access.

BACKGROUND: Prior authorization (PA) is intended to support appropriate use and spending of services and medications, yet 1 in 6 insured adults report...

Elevated pro-BNP and low-grade inflammation are associated with low bone mineral density in systemic sclerosis, a case control study.

BACKGROUND: Bone mineral density (BMD) is compromised in patients with systemic sclerosis (SSc) compared to the background population, yet the underly...

Evaluation of Artificial Intelligence (AI) for Myocardial Infarction Health Information: Expert Accuracy Assessment and User Trust Survey.

BACKGROUND: Artificial intelligence chatbots, particularly ChatGPT, have emerged as increasingly popular sources of health information for the general...

Comparison of artificial intelligence and multidisciplinary team assessment for evaluating biologic decisions in severe uncontrolled asthma.

BACKGROUND: The management of severe asthma with biologics has become more complex involving multidisciplinary team meetings. Artificial intelligence ...

Evolution of Generative Artificial Intelligence in Clinical Practice: Comparative Performance of OpenEvidence 2.0 and ChatGPT-4o.

BACKGROUND CONTEXT: Generative artificial intelligence (AI) is increasingly used in spine care; however, concerns remain regarding citation hallucinat...

Integrating Artificial Intelligence into Venous Thromboembolism Care: Predictive Models, Implementation Challenges, and Future Directions.

Artificial intelligence (AI) has the potential to support personalized, multidisciplinary, data-driven care for venous thromboembolism (VTE) preventio...

Turkish Adaptation of the Nursing Students' Fear Toward Artificial Intelligence Scale: A Study of Validity and Reliability.

Background and Purpose: Most nursing students report having limited knowledge about artificial intelligence, which may lead to anxiety and fear regard...

Clinical Implementation and Validation of Automated Slice-to-Volume Reconstruction for Fetal MRI Using a Vendor-Neutral MONAI-Based Imaging Informatics Pipeline.

This study aims to evaluate the clinical performance and operational reliability of a fully automated, vendor-neutral imaging informatics pipeline for...

Objective technical skills assessment in laparoscopic cholecystectomy: a systematic review of manual, kinematic, and AI-based tools.

BACKGROUND: Technical errors during surgery are a major contributor to preventable adverse outcomes, driving demand for objective assessment tools. La...

Revealing the Link Between Critical Thinking Disposition and Learning Approaches: A Cross-Sectional Study Among Chinese Medical Students.

This study aimed to explore the association between medical students' critical thinking (CT) disposition and learning approach (LA), to provide novel ...

Eliminating Registration Bias in Synthetic CT Generation using a physics-based simulation framework for pelvic anatomy.

Supervised synthetic computed tomography (sCT) generation from cone-beam CT (CBCT) requires spatially registered training pairs, yet perfect registrat...

Visual Signal Typing in Voice Assessment: A Systematic Review of Methods, Reliability, and Clinical Applications.

Acoustic analysis is a fundamental step in the multidimensional assessment of dysphonia. However, conventional perturbation measures require nearly pe...

Integrating generative AI into physiotherapy education: students' use, perceptions, and generative AI literacy following curricular adaptations: a repeated cross-sectional programme evaluation.

BACKGROUND: Structured generative artificial intelligence (GAI) training has been proposed as an effective approach to strengthen healthcare students'...

Labeling matters: A multicenter machine learning study on visual field progression in Glaucoma.

BACKGROUND: To compare machine learning (ML) performance for detecting visual field (VF) progression across different labeling strategies using a larg...

Artificial Intelligence Answering Patient Questions About Developmental Dysplasia of the Hip: Accuracy, Readability, and Clinical Utility.

INTRODUCTION: Artificial intelligence (AI) tools are increasingly used by patients and caregivers seeking medical information. Developmental dysplasia...

Stigmatizing Language in Gender-Expansive Patient Records: Corpus Development, Disparity Analysis, and Natural Language Processing-Based Detection Study.

BACKGROUND: Stigmatizing language (SL) in electronic health records (EHRs) can influence clinical decision-making, propagate bias across care encounte...