Predictive value of initial FDG-PET features for treatment response and survival in esophageal cancer patients treated with chemo-radiation therapy using a random forest classifier.

In oncology, texture features extracted from positron emission tomography with 18-fluorodeoxyglucose images (FDG-PET) are of increasing interest for predictive and prognostic studies, leading to several tens of features per tumor. To select the best features, the use of a random forest (RF) classifi...

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Main Authors: Paul Desbordes, Su Ruan, Romain Modzelewski, Pascal Pineau, Sébastien Vauclin, Pierrick Gouel, Pierre Michel, Frédéric Di Fiore, Pierre Vera, Isabelle Gardin
Formato: Artigo
Idioma:Inglês
Publicado em: Public Library of Science (PLoS) 2017-01-01
Colecção:PLoS ONE
Acesso em linha:http://europepmc.org/articles/PMC5345816?pdf=render
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