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 language | English |
|---|---|
| Pages (from-to) | 52-59 |
| Number of pages | 8 |
| Journal | Procedia Computer Science |
| Volume | 248 |
| Issue number | C |
| DOIs | |
| Publication status | Published - 2024 |
| Event | 12th Scientific Meeting on International Society for Research on Internet Interventions, ISRII-12 2024 - Limerick, Ireland Duration: 9 Oct 2023 → 14 Oct 2023 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- ChatGPT
- T2DM
- chatbot
- conversational agent
- diabetes
- health literacy
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