Databricks Certified Generative AI Engineer Associate · Free Practice Question Medium

Question 8

A Generative AI Engineer is tasked with building a Retrieval-Augmented Generation (RAG) system for a healthcare organization. The system needs to retrieve patient-specific documents and summarize key findings securely. What are the critical components for building this pipeline? (Choose four)
  • A Low-latency GPU infrastructure for real-time queries.
  • B Secure document retriever with access controls.
  • C Embedding model trained on healthcare datasets.
  • D Classification model for tagging medical conditions.
  • E Summarizer model optimized for clinical reports.
Reveal correct answers

Correct answers: A, B, C, E

Explanation

RAG systems for healthcare require domain-specific embedding models, secure retrievers, summarization capabilities, and high-performance compute resources to ensure accuracy, compliance, and efficiency.

A. Correct: GPUs are essential for efficiently handling the computational demands of retrieval and summarization in real-time applications.

B. Correct: A secure retriever prevents unauthorized access to sensitive patient data and ensures compliance with privacy regulations like HIPAA.

C. Correct: An embedding model trained on domain-specific data ensures that document embeddings align with medical terminology and user queries.

D. Incorrect: While classification may help identify conditions, it is not a mandatory component for RAG pipelines.

E. Correct: Summarization models tailored for clinical text ensure concise and relevant outputs for healthcare professionals.

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