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International consensus on research priorities in hypospadias using a Delphi study approach.
J Pediatr Urol
December 2024
Department of Public Health, College of Health Sciences, QU Health, Qatar University, P.O. Box 2713, Doha, Qatar.
Introduction: Hypospadias is a common congenital anomaly of the male genitalia that poses significant management and treatment challenges. Gaining a comprehensive understanding of priority research questions in hypospadiology will be essential to reach agreement on the optimal approach to assessment, treatment, and outcome prediction for affected patients.
Methods: We employed a consensus-building Delphi method to identify and prioritize research questions in the hypospadias field.
Large Language Models in Worldwide Medical Exams: Platform Development and Comprehensive Analysis.
J Med Internet Res
December 2024
Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China.
Background: Large language models (LLMs) are increasingly integrated into medical education, with transformative potential for learning and assessment. However, their performance across diverse medical exams globally has remained underexplored.
Objective: This study aims to introduce MedExamLLM, a comprehensive platform designed to systematically evaluate the performance of LLMs on medical exams worldwide.
Physician vs. AI-generated messages in urology: evaluation of accuracy, completeness, and preference by patients and physicians.
World J Urol
December 2024
Department of Urology, Baldwin Park Medical Center, Kaiser Permanente, 1011 Baldwin Park Blvd., Baldwin Park, CA, 91706, USA.
Purpose: To evaluate the accuracy, comprehensiveness, empathetic tone, and patient preference for AI and urologist responses to patient messages concerning common BPH questions across phases of care.
Methods: Cross-sectional study evaluating responses to 20 BPH-related questions generated by 2 AI chatbots and 4 urologists in a simulated clinical messaging environment without direct patient interaction. Accuracy, completeness, and empathetic tone of responses assessed by experts using Likert scales, and preferences and perceptions of authorship (chatbot vs.
Editorial: The evolution of minimally invasive urologic surgery: innovations, challenges, and opportunities.
Front Surg
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Department of Urology, University of Southampton, Southampton, United Kingdom.
Integrating artificial intelligence in renal cell carcinoma: evaluating ChatGPT's performance in educating patients and trainees.
Transl Cancer Res
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Division of Urologic Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA.
Background: OpenAI's ChatGPT is a large language model-based artificial intelligence (AI) chatbot that can be used to answer unique, user-generated questions without direct training on specific content. Large language models have significant potential in urologic education. We reviewed the primary data surrounding the use of large language models in urology.
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