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...
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: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.1044358/full |
Similar Items
-
Post-Operative Accelerated-Hypofractionated Chemoradiation With Volumetric Modulated Arc Therapy and Simultaneous Integrated Boost in Glioblastoma: A Phase I Study (ISIDE-BT-2)
by: Marica Ferro, et al.
Published: (2021-02-01) -
New Technologies and Multidisciplinarity as Strategic Factors to Cope With Challenges in Postmastectomy Breast Cancer Radiation Therapy
by: Gabriella Macchia, MD, et al.
Published: (2021-11-01) -
Memantine in the Prevention of Radiation-Induced Brain Damage: A Narrative Review
by: Claudia Scampoli, et al.
Published: (2022-05-01) -
Pain Relief after Stereotactic Radiotherapy of Pancreatic Adenocarcinoma: An Updated Systematic Review
by: Milly Buwenge, et al.
Published: (2022-04-01) -
Clinical Studies on Ultrafractionated Chemoradiation: A Systematic Review
by: Erica Scirocco, et al.
Published: (2021-11-01)