DisEmbed, a 33M-parameter disease-specific embedding model trained on synthetic symptom-disease data, claims state-of-the-art triplet accuracy on three disease benchmarks.
Generalist embedding models are better at short-context clinical semantic search than specialized embedding models, 2024
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DisEmbed: Transforming Disease Understanding through Embeddings
DisEmbed, a 33M-parameter disease-specific embedding model trained on synthetic symptom-disease data, claims state-of-the-art triplet accuracy on three disease benchmarks.