mlsanityData to 14 Oct 2026

A General-purpose AI Avatar in Healthcare

arXiv 2401.12981 ↗First posted 10 Jan 2024cs.CLcited by 1

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Abstract (arXiv)

Recent advancements in machine learning and natural language processing have led to the rapid development of artificial intelligence (AI) as a valuable tool in the healthcare industry. Using large language models (LLMs) as conversational agents or chatbots has the potential to assist doctors in diagnosing patients, detecting early symptoms of diseases, and providing health advice to patients. This paper focuses on the role of chatbots in healthcare and explores the use of avatars to make AI interactions more appealing to patients. A framework of a general-purpose AI avatar application is demonstrated by using a three-category prompt dictionary and prompt improvement mechanism. A two-phase approach is suggested to fine-tune a general-purpose AI language model and create different AI avatars to discuss medical issues with users. Prompt engineering enhances the chatbot's conversational abilities and personality traits, fostering a more human-like interaction with patients. Ultimately, the injection of personality into the chatbot could potentially increase patient engagement. Future directions for research include investigating ways to improve chatbots' understanding of context and ensuring the accuracy of their outputs through fine-tuning with specialized medical data sets.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 4 of its 18 references that are in the map. First posted on arXiv 10 Jan 2024.

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4 of 18 references.

References · 4

  1. 2017Attention Is All You Needcited by 60,361
  2. 2022Large Language Models Encode Clinical Knowledgecited by 1,830
  3. 2023A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPTcited by 619
  4. 2023Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Datacited by 48

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