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End-to-End Reliability of Automated Systems for Diagnostic Data Extraction: A Benchmark Study in Uro-Oncologic Evidence Synthesis
2025-12-31
urology
Title + abstract only
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BackgroundAutomated systems, including large language models, are increasingly used to support data extraction in diagnostic systematic reviews. However, their reliability, safety, and repeatability under realistic extraction conditions remain insufficiently characterized. ObjectiveTo benchmark the end-to-end reliability of automated systems for extracting diagnostic accuracy data from published uro-oncologic studies, with a focus on correctness, abstention behavior in non-derivable scenarios, ...
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