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Facilitating validation of prediction models: a comparison of manual and semi-automated validation using registry-based data of breast cancer patients in the Netherlands.

Cornelia D van Steenbeek | Marissa C van Maaren | Sabine Siesling | Annemieke Witteveen | Xander A A M Verbeek | Hendrik Koffijberg
BMC medical research methodology | 2019

Clinical prediction models are not routinely validated. To facilitate validation procedures, the online Evidencio platform ( https://www.evidencio.com ) has developed a tool partly automating this process. This study aims to determine whether semi-automated validation can reliably substitute manual validation.

Pubmed ID: 31176362

Research resources used in this publication

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This is a list of tools and resources that we have found mentioned in this publication.


Surveillance Epidemiology and End Results (tool)

RRID:SCR_006902

SEER collects cancer incidence data from population-based cancer registries covering approximately 47.9 percent of the U.S. population. The SEER registries collect data on patient demographics, primary tumor site, tumor morphology, stage at diagnosis, and first course of treatment, and they follow up with patients for vital status.There are two data products available: SEER Research and SEER Research Plus. This was motivated because of concerns about the increasing risk of re-identifiability of individuals. The Research Plus databases require more rigorous process for access that includes user authentication through Institutional Account or multiple-step request process for Non-Institutional users.

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PREDiCT (tool)

RRID:SCR_015517

Patient database that contains EEG data sets, executable tasks, and computational tools.

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