AIMC Topic: Patient Education as Topic

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Digital Solutions in HF Education: What Can Patients and Clinicians Gain?

Current heart failure reports
PURPOSE OF REVIEW: Heart failure (HF) imposes an expanding global health burden, necessitating innovative approaches to education for both patients and clinicians. This review evaluates the evolving landscape of digital health tools in HF education a...

Performance of large language models in reporting oral health concerns and side effects in head and neck cancer: a comparative study.

Journal of cancer research and clinical oncology
PURPOSE: With increasing reliance on large language models (LLMs) for health information, this study evaluated reliability and quality, understandability, actionability, readability and misinformation risk of responses from LLMs to oral health concer...

Evaluating the Effectiveness of Generative AI for the Creation of Patient Education Materials on Coronary Heart Disease: A Comparative Study.

JMIR formative research
BACKGROUND: Generative artificial intelligence (AI) has shown great potential in various fields, including health care. However, its application for developing patient education materials (PEMs), particularly for those with coronary heart disease (CH...

Artificial intelligence in anesthesia: comparison of the utility of ChatGPT v/s google gemini large language models in pre-anesthetic education: content, readability and sentiment analysis.

BMC anesthesiology
BACKGROUND: Large Language Models (LLMs) such as ChatGPT and Google Gemini are increasingly explored for their potential in patient education, particularly in the perioperative setting. As text-based tools trained on extensive datasets, they can gene...

Utility and Limitations of Large Language Models to Simplify Online Content on Generalized Pustular Psoriasis.

Rhode Island medical journal (2013)
Online health information (OHI) in dermatology often exceeds the recommended sixth-grade reading level, hindering patient comprehension. This study aimed to assess the utility of three artificial intelligence large language models (LLMs) - ChatGPT-3....

Large language model chatbots for patient education in kidney stones: a scoping review.

World journal of urology
PURPOSE: In 2024, 17% of adults reported using an artificial intelligence (AI) chatbot at least once a month as a source of health information, rising to 25% among those under 30. We aim to conduct a scoping review of the existing literature assessin...

Exploring Patient Perspectives, Engagement, and Output Quality in Doctor-Supervised Use of Artificial Intelligence During Informed Consent Consultation With ChatGPT and Retrieval Augmented Generation (RAG): Quantitative Exploratory Study.

Journal of medical Internet research
BACKGROUND: Comprehensive preoperative education is essential for optimizing outcomes and ensuring informed consent in patients undergoing total hip arthroplasty (THA). Emerging artificial intelligence (AI) tools, such as ChatGPT, offer scalable supp...

A comparative analysis of ChatGPT and Google in providing quality and clinical relevance of responses to patients' frequently asked questions on robotic-assisted total knee arthroplasty.

Archives of orthopaedic and trauma surgery
INTRODUCTION: The purpose of this study was to identify the most frequent questions a patient might encounter in an internet search about robotic-assisted total knee arthroplasty (RATKA), and to identify and categorize the answers to these questions ...

Quality assessment of patient-facing urologic telesurgery content using validated tools.

Journal of robotic surgery
INTRODUCTION: With increasing accessibility to Artificial Intelligence (AI) chatbots, the precision and clarity of medical information provided require rigorous assessment. Urologic telesurgery represents a complex concept that patients will investig...

From digital assistants to clinical partners: revolutionizing pediatric urology through large language model-powered decision support and patient education.

World journal of urology
BACKGROUND: Large language models (LLMs) demonstrate increasing potential in healthcare applications, yet their clinical utility in specialized pediatric medicine remains inadequately characterized. This study evaluated LLM performance in pediatric u...