CLJan 10, 2024

A General-purpose AI Avatar in Healthcare

arXiv:2401.12981v14 citationsh-index: 2
Originality Synthesis-oriented
AI Analysis

This work addresses the need for more engaging AI tools in healthcare for patients, but it is incremental as it builds on existing LLM and chatbot technologies.

The paper tackled the problem of making AI interactions in healthcare more appealing by using avatars and prompt engineering, resulting in a framework for creating general-purpose AI avatars with enhanced conversational abilities to potentially increase patient engagement.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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