Abstract
Several studies have indicated that magnetic resonance imaging radiomics can predict survival in patients with breast cancer, but the potential biological underpinning remains indistinct. This study aims to develop an interpretable deep-learning-based network for classifying recurrence risk and revealing the potential biological underpinning.
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