Cluster-based histopathology phenotype representation learning by self-supervised multi-class-token hierarchical ViT.

Abstract excerpt

Developing a clinical AI model necessitates a significant amount of highly curated and carefully annotated dataset by multiple medical experts, which results in increased development time and costs. Self-supervised learning (SSL) is a method that enables AI models to leverage unlabelled data to acquire domain-specific background knowledge that can enhance their performance on various downstream tasks. In this...

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