Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study.

Preoperative risk stratification in endometrial cancer (ENDORISK) by a Bayesian network model: A development and validation study.

BACKGROUND:Bayesian networks (BNs) are machine-learning-based computational models that visualize causal relationships and provide insight into the processes underlying disease progression, closely resembling clinical decision-making. Preoperative identification of patients at risk for lymph node me...

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Main Authors: Casper Reijnen, Evangelia Gogou, Nicole C M Visser, Hilde Engerud, Jordache Ramjith, Louis J M van der Putten, Koen van de Vijver, Maria Santacana, Peter Bronsert, Johan Bulten, Marc Hirschfeld, Eva Colas, Antonio Gil-Moreno, Armando Reques, Gemma Mancebo, Camilla Krakstad, Jone Trovik, Ingfrid S Haldorsen, Jutta Huvila, Martin Koskas, Vit Weinberger, Marketa Bednarikova, Jitka Hausnerova, Anneke A M van der Wurff, Xavier Matias-Guiu, Frederic Amant, ENITEC Consortium, Leon F A G Massuger, Marc P L M Snijders, Heidi V N Küsters-Vandevelde, Peter J F Lucas, Johanna M A Pijnenborg
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-05-01
Series:PLoS Medicine
Online Access:https://doi.org/10.1371/journal.pmed.1003111

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https://doi.org/10.1371/journal.pmed.1003111

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