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A General-purpose AI Avatar in Healthcare (2401.12981v1)

Published 10 Jan 2024 in cs.CL

Abstract: Recent advancements in machine learning and natural language processing have led to the rapid development of AI as a valuable tool in the healthcare industry. Using 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 LLM 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.

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Authors (2)
  1. Nicholas Yan (3 papers)
  2. Gil Alterovitz (3 papers)
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