Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics

Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics

BackgroundRadiomics can provide in-depth characterization of cancers for treatment outcome prediction. Conventional radiomics rely on extraction of image features within a pre-defined image region of interest (ROI) which are typically fed to a classification algorithm for prediction of a clinical en...

Full description

Bibliographic Details
Main Authors: Bao Ngoc Huynh, Aurora Rosvoll Groendahl, Oliver Tomic, Kristian Hovde Liland, Ingerid Skjei Knudtsen, Frank Hoebers, Wouter van Elmpt, Eirik Malinen, Einar Dale, Cecilia Marie Futsaether
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-08-01
Series:Frontiers in Medicine
Subjects:
machine learning
deep learning
artificial intelligence
feature selection
radiomics
head and neck cancer
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2023.1217037/full

Internet

https://www.frontiersin.org/articles/10.3389/fmed.2023.1217037/full

Similar Items