Machine-learning prediction model for acute skin toxicity after breast radiation therapy using spectrophotometry

Machine-learning prediction model for acute skin toxicity after breast radiation therapy using spectrophotometry

PurposeRadiation-induced skin toxicity is a common and distressing side effect of breast radiation therapy (RT). We investigated the use of quantitative spectrophotometric markers as input parameters in supervised machine learning models to develop a predictive model for acute radiation toxicity.Met...

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Bibliographic Details
Main Authors: Savino Cilla, Carmela Romano, Gabriella Macchia, Mariangela Boccardi, Donato Pezzulla, Milly Buwenge, Augusto Di Castelnuovo, Francesca Bracone, Amalia De Curtis, Chiara Cerletti, Licia Iacoviello, Maria Benedetta Donati, Francesco Deodato, Alessio Giuseppe Morganti
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-01-01
Series:Frontiers in Oncology
Subjects:
machine learning
radiation oncology
breast
toxicity
spectrophotometry
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.1044358/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2022.1044358/full

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