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Contrastive Learning for Rare Disease Side Effect Phenotype Clustering

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Deep Learning for Drug Side Effect Repurposing

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Ai Drug Repurposing › Deep Learning for Drug Side Effect Repurposing

Contrastive Learning for Rare Disease Side Effect Phenotype Clustering

This research implements self-supervised contrastive learning on sparse rare disease datasets to cluster similar adverse event phenotypes across drug classes. The methodology generates novel disease-drug associations by recognizing that rare adverse effects may represent undiagnosed therapeutic opportunities.

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📚 Academic: Thesis & PPT assistance included🧪 Tech: Master the protocols hands-on📝 Research > 3 months: Publication co-authorship in a Scopus-indexed journal

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