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...
Main Authors: | , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2017-01-01
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Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC5345816?pdf=render |