Interpretable model based on MRI radiomics to predict the expression of Ki-67 in breast cancer

Interpretable model based on MRI radiomics to predict the expression of Ki-67 in breast cancer

Abstract This study aimed to develop an interpretable machine learning model that accurately predicts Ki-67 expression in breast cancer (BC) patients using a combination of dynamic-contrast enhanced magnetic resonance imaging (DCE-MRI) radiomics and clinical-imaging features. A total of 195 BC patie...

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Bibliographic Details
Main Authors: Li Zhang, Qinglin Du, Mengyi Shen, Xin He, Dingyi Zhang, Xiaohua Huang
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Breast cancer
Ki-67
MRI
Interpretable machine learning
Online Access:https://doi.org/10.1038/s41598-025-97247-1
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https://doi.org/10.1038/s41598-025-97247-1

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