A General-purpose AI Avatar in Healthcare
Nicholas Yan Gil Alterovitz
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.