Artificial Intelligence-Driven Innovations in Chronic Disease Management: From Predictive Modeling to Clinical Implementation

Abstract:

Chronic diseases (e.g., diabetes, hypertension, cardiovascular diseases) pose a global healthcare burden, with aging populations and urbanization exacerbating resource constraints. This study explores how artificial intelligence (AI) technologies—including machine learning (ML), natural language processing (NLP), and wearable sensor analytics—address unmet needs in chronic disease management. We systematically evaluate 12 clinical trials (2022–2025) across 8 countries, demonstrating that AI-driven predictive models reduce hospital readmission rates by 28–35% and improve patient adherence by 40% compared to conventional care. Ethical considerations, including data privacy and algorithmic bias, are integrated into a proposed governance framework. Findings highlight AI’s potential to enhance equitable healthcare delivery amid urbanization-related health challenges.