INTRODUCTION: Electronic patient messaging utilization has increased in recent years and has been associated with physician burnout. ChatGPT is a language model that has shown the ability to generate near-human level text responses. This study evalua...
PURPOSE: Large language models (LLMs) are a form of artificial intelligence (AI) that uses deep learning techniques to understand, summarize and generate content. The potential benefits of LLMs in healthcare is predicted to be immense. The objective ...
PURPOSE: This cross-sectional study assessed a generative artificial intelligence platform to automate the creation of accurate, appropriate, and compelling social media (SoMe) posts from urological journal articles.
Video-based educational programs offer a promising avenue to augment surgical preparation, allow for targeted feedback delivery, and facilitate surgical coaching. Recently, developments in surgical intelligence and computer vision have allowed for au...
Categorization of patients according to their characteristics may simplify decision-making, but it fails to account for the continuous nature of risk and individual variability. Artificial intelligence has the ability to handle more complex continuou...
PURPOSE: Assessments in medical education play a central role in evaluating trainees' progress and eventual competence. Generative artificial intelligence is finding an increasing role in clinical care and medical education. The objective of this stu...
INTRODUCTION: Artificial intelligence technology has a wide range of application prospects in the field of medical education. The aim of the study was to measure the effectiveness of ChatGPT-assisted problem-based learning (PBL) teaching for urology ...
AIMS: The integration of artificial intelligence (AI) into functional urology management must be assessed for its clinical utility, but hopefully will change, perhaps to revolutionize the way LUTD and other conditions are assessed, the aim being to o...
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) methods are increasingly being applied in pediatric urology across a growing number of settings, with more extensive databases and wider interest for use in clinical practice. More th...