TILE
AI Foundation Models for Better Cancer Care
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We can learn from pathology images without human labels through our novel self-supervised learning paradigm.
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Through our self-supervised digital pathology AI workflow, we have discovered a proprietary language of cancer.
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We can understand tumour samples written in our language of cancer, using language models to understand the context and relationship of important histology features.