Personalized predictions of neoadjuvant chemotherapy response in breast cancer using machine learning and full-field digital mammography radiomics

Personalized predictions of neoadjuvant chemotherapy response in breast cancer using machine learning and full-field digital mammography radiomics

ObjectiveThis study aimed to develop a comprehensive nomogram model by integrating clinical pathological and full-field digital mammography (FFDM) radiomic features to predict the efficacy of neoadjuvant chemotherapy (NAC) in breast cancer patients, thereby providing personalized treatment recommend...

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Bibliographic Details
Main Authors: Ye Ruan, Xingyuan Liu, Yantong Jin, Mingming Zhao, Xingda Zhang, Xiaoying Cheng, Yang Wang, Siwei Cao, Menglu Yan, Jianing Cai, Mengru Li, Bo Gao
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Medicine
Subjects:
breast cancer
radiomics
neoadjuvant chemotherapy
machine learning
full-field digital mammography
nomogram
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1582560/full
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