International Neurourology Journal · Published 2026-05-28 · DOI 10.5213/inj.2652134.067
Sung-Jong Eun, Jong Mok Park, Yong Gil Na
Artificial intelligence (AI) is being applied across healthcare, including disease diagnosis, personalized treatment, and rehabilitation management. In urology, AI research has evolved from traditional machine learning to advanced deep learning and generative models. This review categorizes these developments into 3 primary domains. First, machine learning has been applied to mobile-based platforms for continuous urinary health monitoring and personalized healthcare. Second, deep learning- based diagnostic systems have improved the identification of conditions such as prostatic hyperplasia, ureteral strictures, and urinary stones, thereby supporting clinical decision-making. Finally, generative AI, including large language models and vision transformers, is reshaping medical image analysis through data augmentation and expanding patient education through natural language interactions. This review examines integrated applications of AI in urological diseases and discusses current research trends and future prospects for a digital healthcare ecosystem in urology.
Abstract from DOAJ. Public domain (CC0 1.0).
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Eun, S., Park, J., Na, Y. (2026). From Machine Learning to Generative Artificial Intelligence in Urology: Technological Evolution and Future Perspectives. International Neurourology Journal. https://doi.org/10.5213/inj.2652134.067