Prognostic Value of Transfer Learning Based Features in Resectable Pancreatic Ductal Adenocarcinoma

Prognostic Value of Transfer Learning Based Features in Resectable Pancreatic Ductal Adenocarcinoma

Background: Pancreatic Ductal Adenocarcinoma (PDAC) is one of the most aggressive cancers with an extremely poor prognosis. Radiomics has shown prognostic ability in multiple types of cancer including PDAC. However, the prognostic value of traditional radiomics pipelines, which are based on hand-cra...

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Bibliographic Details
Main Authors: Yucheng Zhang, Edrise M. Lobo-Mueller, Paul Karanicolas, Steven Gallinger, Masoom A. Haider, Farzad Khalvati
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-10-01
Series:Frontiers in Artificial Intelligence
Subjects:
transfer learning
radiomics
prognosis
pancreatic cancer
survival analysis
Online Access:https://www.frontiersin.org/article/10.3389/frai.2020.550890/full

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https://www.frontiersin.org/article/10.3389/frai.2020.550890/full

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