Artificial Intelligence Applications for Automated Data Extraction and Secondary Use of Clinical Information in Uro-oncology: A Systematic Review
In this study, we reviewed how artificial intelligence (AI) is being used to extract information automatically from medical reports on urological cancers. We found that most AI systems can identify important clinical details very accurately, but these are usually tested in only one hospital and not yet shown to work reliably in other settings. This means that while AI has great potential to save time and improve data quality, more testing in everyday clinical practice is needed before it can be used safely and routinely.
Authors
- Christoph Seidel (ORCID: https://orcid.org/0000-0002-6023-6336)
- Julian Greß
- Markus K. Schuler (ORCID: https://orcid.org/0000-0003-0764-1049)
- Florian Schröder
- Gordon Otto
- Shahbaz Khan
- Sebastian Sommer
Institutions
- Universität Hamburg (DE)
- University Medical Center Hamburg-Eppendorf (DE)
- Medizinisches Versorgungszentrum Prof. Mathey, Prof. Schofer (DE)
- Stiftung Oskar Helene Heim (DE)
- Munich Center for Quantum Science and Technology (DE)
- Technical University of Munich (DE)
Publication Details
- Journal
- European Urology Open Science
- Published
- 2026-02-26
- DOI
- https://doi.org/10.1016/j.euros.2026.02.006
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00