A two-agent structure for enhanced reasoning
Our work addresses this problem with a novel strategy based mostly on the interaction of two LLM-driven brokers, which is analogous to how human clinicians sort out administration issues.
The Dialogue Agent is user-facing and outfitted to quickly reply based mostly on its present understanding of the affected person. This agent handles the conversational elements of the interplay, gathering details about the affected person’s situation, addressing their considerations, and constructing rapport. By leveraging pure language processing and empathetic communication methods, the Dialogue Agent ensures a seamless and interesting person expertise.
The Mx Agent (Administration Reasoning Agent) intentionally and repeatedly analyzes the out there info, together with scientific pointers and patient-specific information, to optimize administration of the affected person. Leveraging Gemini’s state-of-the-art long-context capabilities, this agent synthesizes and causes over massive quantities of data — affected person dialogues throughout a number of visits along with lots of of pages of scientific pointers — all of sudden. Utilizing this strategy, it produces structured plans for investigations, remedies, and follow-up care, making an allowance for the most recent medical proof, info gathered throughout earlier visits, and particular person affected person preferences.
