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Healthcare AI2024
HealthCare RAG
Automated, HIPAA-compliant health report generation with RAG over clinical data.
AI Engineer
Problem
Clinicians spend hours turning raw lab reports, imaging notes, and patient histories into readable summaries. HealthCare RAG automates report generation with retrieval-augmented generation over clinical data — context-rich, personalized, and privacy-compliant.
Approach
- Built a RAG pipeline orchestrated with LangChain for multi-step clinical workflows.
- Used domain-specific medical embedding models (BioBERT, PubMedBERT) for accurate retrieval.
- Parsed clinical data — lab reports, imaging notes, patient histories — into a searchable vector store.
- Generated context-aware, per-patient summaries under HIPAA / GDPR data-privacy constraints.
Architecture
- Retrieval-augmented generation with medical embeddings (BioBERT / PubMedBERT).
- LangChain orchestration of multi-step retrieval → reasoning → summary.
- HIPAA / GDPR-compliant data handling with real-time analytics on system performance.
Stack
LangChainRAGBioBERTPubMedBERTPineconeNode.jsTypeScript
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