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Multi Med

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We propose DisCeRn: Disease-Contrastive Representations from Multi-Modal Medical Data, a method for modifying contrastive loss by weighting negative pair of samples differently based on marginally related observed pathologies. The detailed project report can be found here.

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tags: machine learning health self-supervised learning

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