A healthcare company wants to develop a proof-of-concept application that uses Amazon Bedrock to automatically...

Create a dataset that includes 50-100 anonymized patient records. Implement Retrieval Augmented Generation (RAG) with a secure knowledge base. Use a judge model to evaluate accuracy metrics across three foundation models (FMs).

Fine-tune a single foundation model (FM) on patient records. Deploy the FM on Amazon Bedrock. Use Amazon Bedrock AgentCore to configure the FM as an agent. Conduct user testing on 500 company staff members.

Select the most powerful available AWS foundation model (FM). Create a chat interface by using Converse APIs. Test the application on 50-100 actual patient records by using only qualitative feedback from stakeholders. Use a custom web interface to gather real-world performance metrics.

Use the Strands SDK to deploy multiple agents that connect to multiple knowledge bases that contain specialized medical documents. Compare the responses of the agents. Evaluate the integration of the agents with the company ' s existing systems.