A healthcare company is using Amazon Bedrock to build a system to help practitioners make clinical decisions. The system must provide treatment recommendations to physicians based only on approved…

Question

Options

• AIntegrate Amazon Bedrock with Amazon Kendra to retrieve approved documents. Implement
• BDeploy an Amazon Bedrock Knowledge Base and connect it to approved clinical source
• CUse Amazon Bedrock and Amazon Comprehend Medical to extract medical entities. Implement
• DUse an Amazon Bedrock knowledge base with Retrieve API calls and InvokeModel API calls to

• A
  9% (5)
• B
  81% (43)
• C
  6% (3)
• D
  4% (2)

Explanation

Option B is the correct solution because Amazon Bedrock Knowledge Bases with the RetrieveAndGenerate API provide a fully managed Retrieval Augmented Generation (RAG) capability that directly addresses grounding, citation, and hallucination prevention with the least operational overhead. Amazon Bedrock Knowledge Bases automatically manage document ingestion, chunking, embedding, retrieval, and ranking from approved data sources. When used with the RetrieveAndGenerate API, the model is constrained to generate responses only from retrieved, approved clinical documentation, significantly reducing the risk of hallucinations or unsupported claims. The API also returns explicit source citations, which satisfies regulatory and clinical transparency requirements without requiring custom comparison or validation logic. This approach aligns with AWS best practices for healthcare GenAI workloads, where correctness and traceability are critical. Because retrieval and generation are tightly integrated, the system avoids multi-step orchestration, custom verification pipelines, or additional compute layers that would increase latency and maintenance burden.

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