LLM-based Solutions for Healthcare Chatbots: a Comparative Analysis

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Sara Montagna, Gianluca Aguzzi, Stefano Ferretti, Martino Francesco Pengo, Lorenz Cuno Klopfenstein, Michelangelo Ungolo, Matteo Magnini
2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), pages 346–351

This paper discusses the challenges of using Large Language Models (LLMs) in medical chatbots for chronic disease self-management. Accordingly, we define an architecture specifically devised to deal with issues related to reliability, clinical trials, and privacy. Two solutions are compared to prevent data disclosure: a filtering mechanism for sensitive data with an external LLM, and a locally deployed LLM using open-source models. Experimental results underscore the challenges in effectively instructing the local LLM so as to provide performances comparable to GPT-3.5.

keywordslarge language model, medical chatbot, chronic disease management
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