Integrative Innovation of Healthcare Informatics and Artificial Intelligence: Applications, Challenges, and Future Directions

Abstract

This paper explores the integrative innovation between healthcare informatics and artificial intelligence (AI), focusing on three core application domains: AI integration in health information systems (HIS and LIS), AI-enabled mobile health (mHealth) and wearable devices, and the construction and application of medical knowledge graphs. Through a comprehensive review of recent literature, case studies, and technical analyses, we examine how AI enhances the efficiency, accuracy, and personalization of healthcare services. Specifically, we discuss the implementation of AI modules in HIS/LIS for clinical decision support and data management, the use of wearable devices and mHealth platforms for real-time chronic disease monitoring and health management guidance, and the role of medical knowledge graphs in literature analysis and disease mechanism interpretation. We also identify key challenges, including data privacy, algorithm bias, and interoperability, and propose future directions to advance this integration. This research contributes to a deeper understanding of how AI can transform healthcare informatics, ultimately improving patient outcomes and healthcare delivery.