We present the first demonstration of a multimodal conversational diagnostic AI agent, Multimodal AMIE. Building on the text-based capabilities of AMIE, which has shown promise in medical diagnostic conversations, this new agent explores how language models can integrate multimodal data during dialogues. Instant messaging platforms, commonly used for sharing images and documents, highlight the importance of incorporating such information in medical discussions. In clinical settings, investigations and tests are crucial for effective care and can significantly influence consultations. The ability to process and discuss multimodal information enhances diagnostic accuracy and clinical decision-making. This innovation addresses the gap in understanding whether large language models (LLMs) can effectively conduct clinical conversations that include complex, multimodal data, paving the way for more advanced and comprehensive AI-driven healthcare solutions.

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