Establishment of an interpretable MRI radiomics-based machine learning model capable of predicting axillary lymph node metastasis in invasive breast cancer

Establishment of an interpretable MRI radiomics-based machine learning model capable of predicting axillary lymph node metastasis in invasive breast cancer

Abstract This study sought to develop a radiomics model capable of predicting axillary lymph node metastasis (ALNM) in patients with invasive breast cancer (IBC) based on dual-sequence magnetic resonance imaging(MRI) of diffusion-weighted imaging (DWI) and dynamic contrast enhancement (DCE) data. Th...

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Bibliographic Details
Main Authors: Dingyi Zhang, Mengyi Shen, Li Zhang, Xin He, Xiaohua Huang
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Breast cancer
Magnetic resonance imaging
Lymph node metastasis
Radiomics
Combined model
SHAP
Online Access:https://doi.org/10.1038/s41598-025-10818-0
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https://doi.org/10.1038/s41598-025-10818-0

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