Predicting tumor recurrence on baseline MR imaging in patients with early-stage hepatocellular carcinoma using deep machine learning

Predicting tumor recurrence on baseline MR imaging in patients with early-stage hepatocellular carcinoma using deep machine learning

Abstract Tumor recurrence affects up to 70% of early-stage hepatocellular carcinoma (HCC) patients, depending on treatment option. Deep learning algorithms allow in-depth exploration of imaging data to discover imaging features that may be predictive of recurrence. This study explored the use of con...

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Bibliographic Details
Main Authors: Ahmet Said Kucukkaya, Tal Zeevi, Nathan Xianming Chai, Rajiv Raju, Stefan Philipp Haider, Mohamed Elbanan, Alexandra Petukhova-Greenstein, MingDe Lin, John Onofrey, Michal Nowak, Kirsten Cooper, Elizabeth Thomas, Jessica Santana, Bernhard Gebauer, David Mulligan, Lawrence Staib, Ramesh Batra, Julius Chapiro
Format: Article
Language:English
Published: Nature Portfolio 2023-05-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-34439-7

Internet

https://doi.org/10.1038/s41598-023-34439-7

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