Advancing AMIE for longitudinal disease management

A two-agent architecture for enhanced reasoning

Our work addresses this challenge with a novel approach based on the interplay of two LLM-driven agents, which has similarities to how human clinicians tackle management problems.

The Dialogue Agent is user-facing and equipped to rapidly respond based on its current understanding of the patient. This agent handles the conversational aspects of the interaction, gathering information about the patient’s condition, addressing their concerns, and building rapport. By leveraging natural language processing and empathetic communication techniques, the Dialogue Agent ensures a seamless and engaging user experience.

The Mx Agent (Management Reasoning Agent) deliberately and continuously analyzes the available information, including clinical guidelines and patient-specific data, to optimize management of the patient. Leveraging Gemini’s state-of-the-art long-context capabilities, this agent synthesizes and reasons over large amounts of information — patient dialogues across several visits in addition to hundreds of pages of clinical guidelines — all at once. Using this approach, it produces structured plans for investigations, treatments, and follow-up care, taking into account the latest medical evidence, information gathered during previous visits, and individual patient preferences.