The Role of Artificial Intelligence in Chronic Disease Care: Implications for Nursing Practice and Radiology Services – A Systematic Review

Abstract

Background: Artificial intelligence (AI) has rapidly emerged as a transformative force in healthcare, particularly in the management of chronic diseases. Its applications span predictive analytics, clinical decision support, personalized care, and advanced diagnostic imaging, with growing relevance to nursing practice and radiology services. Despite increasing interest, the evidence remains fragmented across disciplines.

Objective: This systematic review aimed to synthesize current evidence on the role of AI in chronic disease care, with a specific focus on implications for nursing practice and radiology services.

Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Comprehensive searches were performed across multiple electronic databases to identify peer-reviewed studies examining AI applications in chronic disease management. More than 900 articles were initially identified. After removal of duplicates and rigorous screening of titles, abstracts, and full texts based on predefined inclusion and exclusion criteria, 22 studies were included in the final analysis.

Results: The included studies demonstrated that AI technologies enhance early detection, risk stratification, disease monitoring, and personalized care planning for chronic conditions. In nursing practice, AI-supported tools improved clinical decision-making, workload management, patient education, and continuity of care, while highlighting the importance of human–AI collaboration and ethical considerations. In radiology services, AI contributed to improved diagnostic accuracy, workflow efficiency, image interpretation, and early identification of disease progression, particularly in oncology and cardiometabolic conditions.

Conclusion: AI plays a significant and expanding role in chronic disease care, offering substantial benefits for nursing practice and radiology services. However, successful integration requires robust governance, workforce training, ethical oversight, and alignment with patient-centered care models. Further high-quality studies are needed to evaluate long-term outcomes and real-world implementation.