A radiomic model leveraging conventional and Hessian matrix-based radiomic features from DCE-MRI for predicting efficacy of neoadjuvant chemotherapy in patients with HER2-low breast cancer

Our current study successfully constructed a predictive nomogram that offers a promising strategy for predicting NAC efficacy in patients with HER2-low breast cancer.

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Publication Details

Journal
Frontiers in Medicine
Published
2026-01-13
DOI
https://doi.org/10.3389/fmed.2025.1639977
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

A radiomic model leveraging conventional and Hessian matrix-based radiomic features from DCE-MRI for predicting efficacy of neoadjuvant chemotherapy in patients with HER2-low breast cancer

Qi Wang, Yuwei Zou, Xiaohui Su, Jie Wu et al.
Frontiers in Medicine
Radiomics and Machine Learning in Medical Imaging
article

A radiomic model leveraging conventional and Hessian matrix-based radiomic features from DCE-MRI for predicting efficacy of neoadjuvant chemotherapy in patients with HER2-low breast cancer

Qi Wang, Yuwei Zou, Xiaohui Su, Jie Wu, Meng Lv, Yan Mao, Bingxin Zhao
article en

Abstract

Our current study successfully constructed a predictive nomogram that offers a promising strategy for predicting NAC efficacy in patients with HER2-low breast cancer.

Frontiers in MedicineVol. 12
Qingdao University (CN), Affiliated Hospital of Qingdao University (CN)
Good health and well-being
Openalex Percentile: Top 91%
Radiomics and Machine Learning in Medical Imaging
DOIOpen Access PDFOpenAlex
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A radiomic model leveraging conventional and Hessian matrix-based radiomic features from DCE-MRI for predicting efficacy of neoadjuvant chemotherapy in patients with HER2-low breast cancer — Qi Wang, Yuwei Zou, et al. · Frontiers in Medicine (2026) | TGRS Research Map | TGRS