Analysis of Cross-Combinations of Feature Selection and Machine-Learning Classification Methods Based on [(18)F]F-FDG PET/CT Radiomic Features for Metabolic Response Prediction of Metastatic Breast Cancer Lesions

SIMPLE SUMMARY: Breast cancer is a leading cause of morbidity and mortality worldwide. The metastatic disease is largely responsible for cancer patient deaths, and its treatment implies usually different therapies. In this context, the prediction of response to treatment or depiction of treatment-re...

Descripción completa

Detalles Bibliográficos
Autores principales: Gómez, Ober Van, Herraiz, Joaquin L., Udías, José Manuel, Haug, Alexander, Papp, Laszlo, Cioni, Dania, Neri, Emanuele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9221062/
https://www.ncbi.nlm.nih.gov/pubmed/35740588
http://dx.doi.org/10.3390/cancers14122922

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9221062/
https://www.ncbi.nlm.nih.gov/pubmed/35740588
http://dx.doi.org/10.3390/cancers14122922

Ejemplares similares