You're working on search over clinical text, where keyword matching often misses relevant notes that use different wording for the same concept. You want a representation that captures semantic similarity so related medical phrases can be matched even when the exact terms differ.
How do embeddings work, and how would you use them for medical text search?
Understanding of dense vector representations for textTokenization and preprocessing for clinical languageVector search for semantic retrievalTrade-offs between embeddings and keyword search