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 m...

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Опубликовано в: :PLoS Med
Главные авторы: Reijnen, Casper, Gogou, Evangelia, Visser, Nicole C. M., Engerud, Hilde, Ramjith, Jordache, van der Putten, Louis J. M., van de Vijver, Koen, Santacana, Maria, Bronsert, Peter, Bulten, Johan, Hirschfeld, Marc, Colas, Eva, Gil-Moreno, Antonio, Reques, Armando, Mancebo, Gemma, Krakstad, Camilla, Trovik, Jone, Haldorsen, Ingfrid S., Huvila, Jutta, Koskas, Martin, Weinberger, Vit, Bednarikova, Marketa, Hausnerova, Jitka, van der Wurff, Anneke A. M., Matias-Guiu, Xavier, Amant, Frederic, Massuger, Leon F. A. G., Snijders, Marc P. L. M., Küsters-Vandevelde, Heidi V. N., Lucas, Peter J. F., Pijnenborg, Johanna M. A.
Формат: Artigo
Язык:Inglês
Опубликовано: Public Library of Science 2020
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Research Article
Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC7228042/
https://ncbi.nlm.nih.gov/pubmed/32413043
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pmed.1003111
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