Development of a Machine Learning Model for Optimal Applicator Selection in High-Dose-Rate Cervical Brachytherapy

Development of a Machine Learning Model for Optimal Applicator Selection in High-Dose-Rate Cervical Brachytherapy

PurposeTo develop and validate a preliminary machine learning (ML) model aiding in the selection of intracavitary (IC) versus hybrid interstitial (IS) applicators for high-dose-rate (HDR) cervical brachytherapy.MethodsFrom a dataset of 233 treatments using IC or IS applicators, a set of geometric fe...

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Bibliographic Details
Main Authors: Kailyn Stenhouse, Michael Roumeliotis, Philip Ciunkiewicz, Robyn Banerjee, Svetlana Yanushkevich, Philip McGeachy
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Oncology
Subjects:
gynecologic brachytherapy
intracavitary brachytherapy (ICBT)
high-dose-rate brachytherapy
radiation oncology
machine learning
decision-support tools
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2021.611437/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2021.611437/full

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