Large language models (LLMs) are increasingly being used to search and summarize information in a natural, conversational manner. With the launch of ChatGPT, search has transformed from a single-turn matching of intent to links to a multi-turn experience with context, and richer answers drawn from multiple sources. In this session, we explore the application of Google’s LLMs to provide a semantic search experience over FHIR data and show examples of natural language search over the patient’s longitudinal patient record and other FHIR repositories.
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