Question

A healthcare software company is building an assistant that must reliably interpret and generate highly specialized oncology terminology and follow domain-specific clinical writing conventions. The underlying knowledge (drug names, protocols) is stable and rarely changes. Testing shows a general foundation model misuses terminology and produces text in the wrong clinical style even when relevant reference documents are supplied in the prompt. Which approach best addresses this problem?

Accepted Answer

Fine-tune the foundation model on a curated dataset of oncology text and clinical writing examples

Answer

Implement a Retrieval Augmented Generation pipeline that injects reference documents into each prompt

Answer

Increase the temperature parameter so the model produces more varied terminology

Answer

Add more reference documents to the knowledge base to expand retrieval coverage