Comparison between vision transformers and convolutional neural networks to predict non-small lung cancer recurrence

Comparison between vision transformers and convolutional neural networks to predict non-small lung cancer recurrence

Abstract Non-Small cell lung cancer (NSCLC) is one of the most dangerous cancers, with 85% of all new lung cancer diagnoses and a 30–55% of recurrence rate after surgery. Thus, an accurate prediction of recurrence risk in NSCLC patients during diagnosis could be essential to drive targeted therapies...

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Bibliographic Details
Main Authors: Annarita Fanizzi, Federico Fadda, Maria Colomba Comes, Samantha Bove, Annamaria Catino, Erika Di Benedetto, Angelo Milella, Michele Montrone, Annalisa Nardone, Clara Soranno, Alessandro Rizzo, Deniz Can Guven, Domenico Galetta, Raffaella Massafra
Format: Article
Language:English
Published: Nature Portfolio 2023-11-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-48004-9

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https://doi.org/10.1038/s41598-023-48004-9

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