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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
PURPOSE: 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)...
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| Pubblicato in: | PLoS One |
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| Autori principali: | , , , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Public Library of Science
2017
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5345816/ https://ncbi.nlm.nih.gov/pubmed/28282392 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0173208 |
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