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From Machine Learning to Generative Artificial Intelligence in Urology: Technological Evolution and Future Perspectives

Year: 2026

Type: article

Abstract: 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.

Source: International Neurourology Journal

DOI: 10.5213/inj.2652134.067

Authors: Sung-Jong Eun, Jong Mok Park, Yong Gil Na

Institutions: National IT industry Promotion Agency, Chungnam National University Sejong Hospital

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

Funder: Chungnam National University