Development and Validation of a Radiomics-Based Nomogram for Predicting HER-2 Status in Breast Cancer: A Retrospective Study with Small Validation Cohort

The radiomics-based nomogram developed in this study offers a promising non-invasive tool for predicting HER-2 expression status in breast cancer. By integrating clinical data and advanced MRI features, this model provides accurate predictions, improving personalized treatment strategies. Further validation in larger, multicenter studies is necessary to confirm its generalizability and clinical applicability.

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Publication Details

Journal
Breast Cancer Targets and Therapy
Published
2025-12-01
DOI
https://doi.org/10.2147/bctt.s550088
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Development and Validation of a Radiomics-Based Nomogram for Predicting HER-2 Status in Breast Cancer: A Retrospective Study with Small Validation Cohort

C. Chen, Langlang Tang, Jinyin Chen, Qihong Qiu et al.
Breast Cancer Targets and Therapy
Radiomics and Machine Learning in Medical Imaging
article

Development and Validation of a Radiomics-Based Nomogram for Predicting HER-2 Status in Breast Cancer: A Retrospective Study with Small Validation Cohort

C. Chen, Langlang Tang, Jinyin Chen, Qihong Qiu, Chun-Tao Liao
article en

Abstract

The radiomics-based nomogram developed in this study offers a promising non-invasive tool for predicting HER-2 expression status in breast cancer. By integrating clinical data and advanced MRI features, this model provides accurate predictions, improving personalized treatment strategies. Further validation in larger, multicenter studies is necessary to confirm its generalizability and clinical applicability.

Breast Cancer Targets and TherapyVol. Volume 17
Fujian Medical University (CN), First Affiliated Hospital of Fujian Medical University (CN)
Openalex Percentile: Top 48%
Radiomics and Machine Learning in Medical Imaging
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