Digitale Urologie: Einsatzmöglichkeiten für künstliche Intelligenz und digitale Gesundheitsanwendungen : Leitthema
Background Urology presents itself as a modern and future-oriented discipline. Artificial intelligence (AI) is becoming increasingly important in the field of digital urology. It enables the analysis of large medical data sets, such as histological patterns, imaging or molecular markers. In addition...
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| Main Authors: | , , , , , |
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| Format: | Article (Journal) |
| Language: | German |
| Published: |
September 2025
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| In: |
Die Urologie
Year: 2025, Volume: 64, Issue: 9, Pages: 900-908 |
| ISSN: | 2731-7072 |
| DOI: | 10.1007/s00120-025-02651-0 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1007/s00120-025-02651-0 Verlag, lizenzpflichtig, Volltext: http://link.springer.com/article/10.1007/s00120-025-02651-0 
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| Author Notes: | Emily Rinderknecht, R. Alexa, N. Carl, M. Goertz, F. Wessels, H. Borgmann |
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| 520 | |a Background Urology presents itself as a modern and future-oriented discipline. Artificial intelligence (AI) is becoming increasingly important in the field of digital urology. It enables the analysis of large medical data sets, such as histological patterns, imaging or molecular markers. In addition, large language models (LLMs) are opening up new fields of application. Digital health applications (DiGA) are also becoming increasingly important. Objectives This article provides an overview of current developments in digital urology. The focus is on the possible applications of AI and LLMs, taking into account the legal and ethical framework, as well as an overview of the therapeutic landscape of DiGA in urological care. Methods Existing AI models and applications will be presented and analyzed. In addition, DiGA in urological care and current regulatory requirements are discussed. Results AI systems can improve many areas of urology—for example through automated evaluation of image morphology and histology data or voice-based applications in documentation and communication. DiGA support the follow-up care and treatment of urological diseases. Their use requires transparency, data protection, and quality assurance. Conclusion AI and digital applications offer new care models and can help to increase efficiency. Challenges exist in terms of data quality, information technology infrastructure and the safe and responsible use of technologies. Future developments should be interdisciplinary. | ||
| 546 | |a Sprache der Zusammenfassungen: Deutsch und Englisch | ||
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