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.

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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
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article

Artificial Intelligence Applications for Automated Data Extraction and Secondary Use of Clinical Information in Uro-oncology: A Systematic Review

Christoph Seidel, Julian Greß, Markus K. Schuler, Florian Schröder et al.
European Urology Open Science
Artificial Intelligence in Healthcare and Education
article

Artificial Intelligence Applications for Automated Data Extraction and Secondary Use of Clinical Information in Uro-oncology: A Systematic Review

Christoph Seidel, Julian Greß, Markus K. Schuler, Florian Schröder, Gordon Otto, Shahbaz Khan, Sebastian Sommer
article en

Abstract

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.

European Urology Open ScienceVol. 86
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)
Openalex Percentile: Top 43%
Artificial Intelligence in Healthcare and Education
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Artificial Intelligence Applications for Automated Data Extraction and Secondary Use of Clinical Information in Uro-oncology: A Systematic Review — Christoph Seidel, Julian Greß, et al. · European Urology Open Science (2026) | TGRS Research Map | TGRS