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Towards Explainable Breast Cancer Classification Using SimCLR-Based Self-Supervised Representation Learning

2025-10-12

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<title>Abstract</title> <p>Precise and interpretable histopathology image-based breast cancer classification is of utmost importance for early diagnosis and efficient treatment planning. Conventional deep learning models tend to rely on large annotated datasets and are not interpretable, undermining clinical trust and deployment. In this work, an SSL method with SimCLR contrastive pretraining is utilized to tap t...

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Literature Corpus work: 8c35f2f3-a556-5e1b-b6f5-8ab4fa8ecd38
DOI: 10.21203/rs.3.rs-7812447/v1

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