Artificial intelligence in chronic disease self-management: current applications and future directions

Area of Science:

• Medical Informatics
• Artificial Intelligence in Healthcare
• Digital Health

Background:

• Chronic diseases require continuous self-management support.
• Integrating advanced technologies like artificial intelligence (AI) presents opportunities and challenges.

Purpose of the Study:

• To summarize AI applications in chronic disease self-management.
• To critically evaluate the effectiveness of AI tools.
• To identify implementation barriers and future research directions.

Main Methods:

• A narrative literature review was conducted.
• Databases searched included PubMed, Web of Science, and Scopus.
• Studies on AI-enabled chronic disease self-management tools were synthesized thematically.

Main Results:

• AI functions include personalized decision support, continuous monitoring, conversational agents, and AI-enabled mobile health (mHealth) platforms.
• Key challenges include data privacy, algorithmic bias, interoperability, user engagement, and the digital divide.
• Limited high-quality evidence on clinical and cost-effectiveness was noted.

Conclusions:

• Future AI development should focus on accuracy, explainability, and trustworthiness.
• Enhanced clinical integration and rigorous evaluation are crucial.
• Addressing ethical and implementation barriers is essential to maximize AI's potential in chronic disease care.