Large language models encode clinical knowledge and can answer medical expert questions out-of-the-box without further training. However, this zero-shot performance is limited by outdated training data and lack of explainability impeding clinical translation. We aimed to develop a urology-specialized chatbot (UroBot) and evaluate it against state-of-the-art models as well as historical urologists’ performance in answering urological board questions in a fully clinician-verifiable manner.

ESMO Real-World Data and Digital Oncology is the European Society for Medical Oncology’s latest peer-reviewed open access journal. It is dedicated to publishing high-quality data science and educational content on the transformation of oncology care with real-world evidence and digital technologies that physicians can trust and understand. The journal will publish innovative research that provides actionable insights from real-world data sources and digital devices, such as generalizable observational