Integrating multiparametric MRI radiomics and clinical models to assess sensitivity to neoadjuvant chemotherapy in breast cancer: A multicenter study

The SHAP-explainable radiomic-clinical model provides a clinically applicable, noninvasive tool for pretreatment stratification of NAC sensitivity. This approach enhances personalized therapeutic decision-making while minimizing unnecessary treatment toxicity.

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Publication Details

Journal
Journal of Applied Clinical Medical Physics
Published
2025-11-01
DOI
https://doi.org/10.1002/acm2.70347
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
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article

Integrating multiparametric MRI radiomics and clinical models to assess sensitivity to neoadjuvant chemotherapy in breast cancer: A multicenter study

Xinyi Zeng, Jidong Peng, Xiaofei Tang, Jinxin Chen et al.
Journal of Applied Clinical Medical Physics
Radiomics and Machine Learning in Medical Imaging
article

Integrating multiparametric MRI radiomics and clinical models to assess sensitivity to neoadjuvant chemotherapy in breast cancer: A multicenter study

Xinyi Zeng, Jidong Peng, Xiaofei Tang, Jinxin Chen, Xianjun Zeng
article en

Abstract

The SHAP-explainable radiomic-clinical model provides a clinically applicable, noninvasive tool for pretreatment stratification of NAC sensitivity. This approach enhances personalized therapeutic decision-making while minimizing unnecessary treatment toxicity.

Journal of Applied Clinical Medical PhysicsVol. 26(11)
Nanchang University (CN), Ganzhou People's Hospital (CN), First Affiliated Hospital of Nanchang University (CN)
Openalex Percentile: Top 50%
Radiomics and Machine Learning in Medical Imaging
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