Leveraging MRI radiomics signature for predicting the diagnosis of CXCL9 in breast cancer

The utilization of MRI radiomic features for predicting CXCL9 expression level provides a novel non-invasive approach for breast cancer Prognostic research.

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Publication Details

Journal
Heliyon
Published
2024-09-28
DOI
https://doi.org/10.1016/j.heliyon.2024.e38640
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Leveraging MRI radiomics signature for predicting the diagnosis of CXCL9 in breast cancer

Liping Yan, Yuexia Chen, Jianxin He
Heliyon
Radiomics and Machine Learning in Medical Imaging
article

Leveraging MRI radiomics signature for predicting the diagnosis of CXCL9 in breast cancer

Liping Yan, Yuexia Chen, Jianxin He
article en

Abstract

The utilization of MRI radiomic features for predicting CXCL9 expression level provides a novel non-invasive approach for breast cancer Prognostic research.

HeliyonVol. 10(19)
Nanchang University (CN), Jiangxi Maternal and Child Health Hospital (CN), Third Hospital of Nanchang (CN), First Affiliated Hospital of GuangXi Medical University (CN), First Affiliated Hospital of Nanchang University (CN)
Good health and well-being
Openalex Percentile: Top 72%
Radiomics and Machine Learning in Medical Imaging
DOIOpen Access PDFOpenAlex
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