A Two-Step Feature Selection Radiomic Approach to Predict Molecular Outcomes in Breast Cancer

A Two-Step Feature Selection Radiomic Approach to Predict Molecular Outcomes in Breast Cancer

Breast Cancer (BC) is the most common cancer among women worldwide and is characterized by intra- and inter-tumor heterogeneity that strongly contributes towards its poor prognosis. The Estrogen Receptor (ER), Progesterone Receptor (PR), Human Epidermal Growth Factor Receptor 2 (HER2), and Ki67 anti...

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Bibliographic Details
Main Authors: Valentina Brancato, Nadia Brancati, Giusy Esposito, Massimo La Rosa, Carlo Cavaliere, Ciro Allarà, Valeria Romeo, Giuseppe De Pietro, Marco Salvatore, Marco Aiello, Mara Sangiovanni
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Sensors
Subjects:
radiomics
Breast Cancer
machine learning
feature selection
Online Access:https://www.mdpi.com/1424-8220/23/3/1552

Internet

https://www.mdpi.com/1424-8220/23/3/1552

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