Google’s latest paper on AMIE (Video) gives us a look at the system architecture required to make multimodal telehealth work.

Instead of forcing one model to do everything, they decoupled the workflow into a multi-agent system running in parallel:

1️⃣ Talker Agent: Manages sub-second, patient-facing dialogue without awkward delays.
2️⃣ Perception Agent: Processes live video and audio to spot non-verbal signs and instruct physical exam maneuvers.
3️⃣ Planner Agent: Handles heavy diagnostic reasoning and guideline checks in the background.

The results in actor-based OSCE scenarios were impressive.

Top-1 diagnostic accuracy hit ~91% compared to ~77% for primary care physicians, and the model was surprisingly proactive at positioning the camera for physical exams. 🩺

A few reality checks worth keeping in mind:

⚠️ Actors vs. Real Patients: Controlled scripts don't capture messy real-world edge cases, overlapping comorbidities, or bad lighting.
⚠️ Fine Visuals: The system still misses subtle physical cues like mild nystagmus or slight tremors.
⚠️ Empathy: Human doctors still held the edge in building natural therapeutic rapport and clinical partnership.

🤝I don't see this as autonomous care. I see it as smart intake and ingestion.

⚡An AI assistant handles the pre-visit video triage, gathers structured history, and hands a prepped summary to the doctor could eliminate a ton of administrative friction. A more advanced, holistic version of what I worked on with Ubie.

Would you let an AI handle the first 5 minutes of your next virtual doctor visit? 🤖

Read the paper here: https://arxiv.org/abs/2608.09861

#ArtificialIntelligence #SystemArchitecture #MedicalAI #Gemini #HealthTech #DigitalHealth #Telehealth

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