INTRODUCTION: There are barriers that exist for individuals to adhere to cardiovascular rehabilitation programs. A key driver to patient adherence is appropriately educating patients. A growing education tool is using large language models to answer ...
The journal of international advanced otology
39936545
Background: Tympanoplasty, essential for repairing tympanic membrane perforations, requires careful postoperative care for successful recovery. However, timely access to healthcare guidance can be challenging, especially in rural or underserved areas...
OBJECTIVE: This study aimed to assess people's preference between traditional and Artificial Intelligence (AI)-generated colon cancer staging Patient Education Materials (PEMs).
OBJECTIVES: The aim of this study was to assess the accuracy and readability of the answers generated by large language model (LLM)-chatbots to common patient questions about low back pain (LBP).
Journal of ISAKOS : joint disorders & orthopaedic sports medicine
39988021
INTRODUCTION: Over 61% of Americans seek health information online, often using artificial intelligence (AI) tools like ChatGPT. However, concerns persist about the readability and accessibility of AI-generated content, especially for individuals wit...
INTRODUCTION: Diabetes self-management education (DSME) is endorsed by the American Diabetes Association (ADA) as an essential component of diabetes management. However, the utilization of DSME remains limited in the USA. This study aimed to investig...
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
39957550
AIM(S): To determine the correlation between preoperative health education and the emotions of lung cancer patients, artificial intelligence software was used.
PURPOSE OF REVIEW: Artificial intelligence (AI) chatbots are increasingly used as a source of information. Our objective was to review the literature on their use for patient education in urology.
BACKGROUND: Adequate patient awareness and understanding of cancer clinical trials is essential for trial recruitment, informed decision making, and protocol adherence. Although large language models (LLMs) have shown promise for patient education, t...