Electron Density and Biologically Effective Dose (BED) Radiomics-Based Machine Learning Models to Predict Late Radiation-Induced Subcutaneous Fibrosis

Purpose: to predict the occurrence of late subcutaneous radiation induced fibrosis (RIF) after partial breast irradiation (PBI) for breast carcinoma by using machine learning (ML) models and radiomic features from 3D Biologically Effective Dose (3D-BED) and Relative Electron Density (3D-RED). Method...

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Detalles Bibliográficos
Autores principales: Avanzo, Michele, Pirrone, Giovanni, Vinante, Lorenzo, Caroli, Angela, Stancanello, Joseph, Drigo, Annalisa, Massarut, Samuele, Mileto, Mario, Urbani, Martina, Trovo, Marco, el Naqa, Issam, De Paoli, Antonino, Sartor, Giovanna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7186445/
https://www.ncbi.nlm.nih.gov/pubmed/32373520
http://dx.doi.org/10.3389/fonc.2020.00490

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