Building and Beta-Testing Be Well Buddy Chatbot, a Secure, Credible and Trustworthy AI Chatbot That Will Not...

Area of Science:

• Artificial Intelligence in Healthcare
• Natural Language Processing
• Machine Learning

Background:

• Generative AI chatbots like ChatGPT are increasingly used in healthcare for patient education but pose risks of misinformation.
• Healthcare systems require secure and credible AI tools for patient education, access to care, and self-management.
• Ensuring data security and privacy is paramount for AI adoption in healthcare settings.

Purpose of the Study:

• To develop a secure AI-powered system for SMS-based substance use disorder (SUD) screening and information provision.
• To ensure reliable and trustworthy encryption of protected health information (PHI) for data transfer via third-party vendors.
• To create a user-friendly platform for accessing SUD information and treatment services.

Main Methods:

• Building an AI chatbot utilizing natural language processing (NLP) and machine learning (ML) for classifying expert-curated SUD content.
• Implementing Health Insurance Portability and Accountability Act (HIPAA) compliant data encryption for data transfer and data at rest.
• Designing a dynamic, user-driven conversational interface for SUD dialogue, screening, and treatment access.

Main Results:

• The AI chatbot system effectively classifies SUD-related content using NLP and ML.
• Demonstrated compliance with HIPAA regulations for data encryption, ensuring secure handling of PHI.
• The system provides a state-of-the-art, secure platform for user engagement regarding SUD.

Conclusions:

• The developed AI chatbot system is timely and relevant, addressing the need for secure digital health tools.
• The study advances the field of AI in healthcare by providing a secure and credible solution for substance use disorder management.
• User-friendly design and adherence to digital rights regulations are crucial for the successful implementation of digital health offerings.