Prediction of Chemotherapy Response in Locally Advanced Breast Cancer Patients at Pre-Treatment Using CT Textural Features and Machine Learning: Comparison of Feature Selection Methods

Prediction of Chemotherapy Response in Locally Advanced Breast Cancer Patients at Pre-Treatment Using CT Textural Features and Machine Learning: Comparison of Feature Selection Methods

Rationale: Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response of NAC for patients with LABC before initiating treatment would be valuable to customize therapies and ensure the delivery of effective care. Objective: Our obje...

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Bibliographic Details
Main Authors: Amir Moslemi, Laurentius Oscar Osapoetra, Archya Dasgupta, Schontal Halstead, David Alberico, Maureen Trudeau, Sonal Gandhi, Andrea Eisen, Frances Wright, Nicole Look-Hong, Belinda Curpen, Michael Kolios, Gregory J. Czarnota
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Tomography
Subjects:
NAC
LABC
CT imaging
textural features
machine learning
Online Access:https://www.mdpi.com/2379-139X/11/3/33
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