Predicting Neoadjuvant Treatment Response in Triple-Negative Breast Cancer Using Machine Learning

Predicting Neoadjuvant Treatment Response in Triple-Negative Breast Cancer Using Machine Learning

Background: Neoadjuvant chemotherapy (NAC) is the standard treatment for early-stage triple negative breast cancer (TNBC). The primary endpoint of NAC is a pathological complete response (pCR). NAC results in pCR in only 30–40% of TNBC patients. Tumor-infiltrating lymphocytes (TILs), Ki67 and phosph...

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Bibliographic Details
Main Authors: Shristi Bhattarai, Geetanjali Saini, Hongxiao Li, Gaurav Seth, Timothy B. Fisher, Emiel A. M. Janssen, Umay Kiraz, Jun Kong, Ritu Aneja
Format: Article
Language:English
Published: MDPI AG 2023-12-01
Series:Diagnostics
Subjects:
triple-negative breast cancer
neoadjuvant chemotherapy
machine learning
prediction model
Online Access:https://www.mdpi.com/2075-4418/14/1/74

Internet

https://www.mdpi.com/2075-4418/14/1/74

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