Interpretable Machine Learning Model for Locoregional Relapse Prediction in Oropharyngeal Cancers

SIMPLE SUMMARY: Machine learning may be used to personalize cancer care. However, physicians need interpretability to understand and use a predictive model powered by machine learning. We present a radiomics based model, interpretable for each patient, trained on an American multicentric cohort that...

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Detalles Bibliográficos
Autores principales: Giraud, Paul, Giraud, Philippe, Nicolas, Eliot, Boisselier, Pierre, Alfonsi, Marc, Rives, Michel, Bardet, Etienne, Calugaru, Valentin, Noel, Georges, Chajon, Enrique, Pommier, Pascal, Morelle, Magali, Perrier, Lionel, Liem, Xavier, Burgun, Anita, Bibault, Jean Emmanuel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795920/
https://www.ncbi.nlm.nih.gov/pubmed/33379188
http://dx.doi.org/10.3390/cancers13010057

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7795920/
https://www.ncbi.nlm.nih.gov/pubmed/33379188
http://dx.doi.org/10.3390/cancers13010057

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