Machine learning prediction of pathological complete response to neoadjuvant chemotherapy with peritumoral breast tumor ultrasound radiomics: compare with intratumoral radiomics and clinicopathologic predictors

Authors

Wei Zhou (ORCID: https://orcid.org/0000-0002-6748-6303)
Jiejie Yao (ORCID: https://orcid.org/0000-0002-2437-9444)
Ying Zhu (ORCID: https://orcid.org/0000-0002-5502-3571)
Jianqiao Zhou (ORCID: https://orcid.org/0009-0009-0137-4657)
Weiwei Zhan (ORCID: https://orcid.org/0000-0002-2015-4627)
Xiaosong Chen (ORCID: https://orcid.org/0000-0002-3286-0035)
Xiaohong Jia

Institutions

Ruijin Hospital (CN)

Publication Details

Journal: Breast Cancer Research and Treatment
Published: 2025-05-16
DOI: https://doi.org/10.1007/s10549-025-07727-1
Citations: 1
Primary Topic: Radiomics and Machine Learning in Medical Imaging
Type: article
Field-Weighted Citation Impact: 1.36

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article

Machine learning prediction of pathological complete response to neoadjuvant chemotherapy with peritumoral breast tumor ultrasound radiomics: compare with intratumoral radiomics and clinicopathologic predictors

Wei Zhou, Jiejie Yao, Ying Zhu, Jianqiao Zhou et al.

May 16, 2025

1 citations

Breast Cancer Research and Treatment

Radiomics and Machine Learning in Medical Imaging

1.36

article

Machine learning prediction of pathological complete response to neoadjuvant chemotherapy with peritumoral breast tumor ultrasound radiomics: compare with intratumoral radiomics and clinicopathologic predictors

Wei Zhou, Jiejie Yao, Ying Zhu, Jianqiao Zhou, Weiwei Zhan, Xiaosong Chen, Xiaohong Jia

May 16, 2025article en

1 citations

Abstract

No abstract available for this paper.

Breast Cancer Research and TreatmentVol. 212(2)

Ruijin Hospital (CN)

Good health and well-being

Openalex Percentile: Top 20%

Radiomics and Machine Learning in Medical Imaging

1.36

DOI Open Access PDF OpenAlex

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