Design, architecture and safety evaluation of an AI chatbot for an educational approach to health promotion in chronic medical conditions

Anthony Kelly, Eoin Noctor, Pepijn Van De Ven

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper presents the design, architecture, and safety evaluation of an AI chatbot tailored for educational purposes in man aging chronic medical conditions, focusing on Type 2 Diabetes Mellitus (T2DM). Leveraging conversational agents in health literacy, the chatbot integrates medically informed information, constrained responses, and response traceability to ensure appropriateness and compliance with protocols. By utilizing ChatGPT with retrieval augmented generation (RAG) and careful prompt engineering, the system ensures reliable, traceable, and privacy-conscious interactions. Safety and efficacy testing revealed just one inappropriate response (5%) in a simulated patient conversation and 15 (75%) fully appropriate responses. This study highlights the potential of AI chatbots in enhancing patient autonomy, reliability, and privacy in accessing medical knowledge for chronic conditions.

Original languageEnglish
Pages (from-to)52-59
Number of pages8
JournalProcedia Computer Science
Volume248
Issue numberC
DOIs
Publication statusPublished - 2024
Event12th Scientific Meeting on International Society for Research on Internet Interventions, ISRII-12 2024 - Limerick, Ireland
Duration: 9 Oct 202314 Oct 2023

Keywords

  • chatbot
  • ChatGPT
  • conversational agent
  • diabetes
  • health literacy
  • T2DM

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