Personalized prediction of breast cancer candidates for Anti-HER2 therapy using 18F-FDG PET/CT parameters and machine learning: a dual-center study

Personalized prediction of breast cancer candidates for Anti-HER2 therapy using 18F-FDG PET/CT parameters and machine learning: a dual-center study

BackgroundAccurately evaluating human epidermal growth factor receptor (HER2) expression status in breast cancer enables clinicians to develop individualized treatment plans and improve patient prognosis. The purpose of this study was to assess the performance of a machine learning (ML) model that w...

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Bibliographic Details
Main Authors: Zhenguo Sun, Jianxiong Gao, Wenji Yu, Xiaoshuai Yuan, Peng Du, Peng Chen, Yuetao Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-05-01
Series:Frontiers in Oncology
Subjects:
breast cancer
18 F-FDG PET/CT
HER2
machine learning
SHAP
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2025.1590769/full
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https://www.frontiersin.org/articles/10.3389/fonc.2025.1590769/full

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