Transfer learning approach based on computed tomography images for predicting late xerostomia after radiotherapy in patients with oropharyngeal cancer

Transfer learning approach based on computed tomography images for predicting late xerostomia after radiotherapy in patients with oropharyngeal cancer

Background and purposeAlthough the latest breakthroughs in radiotherapy (RT) techniques have led to a decrease in adverse event rates, these techniques are still associated with substantial toxicity, including xerostomia. Imaging biomarkers could be useful to predict the toxicity risk related to eac...

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Bibliographic Details
Main Authors: Annarita Fanizzi, Giovanni Scognamillo, Alessandra Nestola, Santa Bambace, Samantha Bove, Maria Colomba Comes, Cristian Cristofaro, Vittorio Didonna, Alessia Di Rito, Angelo Errico, Loredana Palermo, Pasquale Tamborra, Michele Troiano, Salvatore Parisi, Rossella Villani, Alfredo Zito, Marco Lioce, Raffaella Massafra
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-09-01
Series:Frontiers in Medicine
Subjects:
deep learning
xerostomia
oropharyngeal cancer
CT images
CNN–convolutional neural network
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2022.993395/full

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https://www.frontiersin.org/articles/10.3389/fmed.2022.993395/full

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