Utilizing conventional MRI to predict molecular subtypes of breast cancer.

This study suggests that cMRI features can help differentiate breast cancer subtypes, such as LA, HER-2, and TNBC, serving as useful supplements to imunohistochemistry and clinical data.

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Publication Details

Journal
PubMed
Published
2025-09-25
DOI
https://doi.org/10.7417/ct.2025.5268
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Utilizing conventional MRI to predict molecular subtypes of breast cancer.

Tran Thi Minh Hue, Nguyen Thu Huong, Nguyen Duy Hung
PubMed
Radiomics and Machine Learning in Medical Imaging
article

Utilizing conventional MRI to predict molecular subtypes of breast cancer.

Tran Thi Minh Hue, Nguyen Thu Huong, Nguyen Duy Hung
article en

Abstract

This study suggests that cMRI features can help differentiate breast cancer subtypes, such as LA, HER-2, and TNBC, serving as useful supplements to imunohistochemistry and clinical data.

PubMedVol. 176(5)
Hanoi Medical University (VN), Vinmec Times City International Hospital (VN), Viet Duc Hospital (VN)
Openalex Percentile: Top 61%
Radiomics and Machine Learning in Medical Imaging
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