Integrating AI-Driven Telemonitoring Systems for Chronic Disease Management: A Path Toward Personalized Digital Healthcare

Abstract

The global rise in chronic diseases such as diabetes, cardiovascular disorders, and respiratory ailments has created an urgent demand for continuous, technology-enabled health management systems. Artificial Intelligence (AI) driven telemonitoring represents a transformative approach that merges remote patient monitoring with intelligent data analytics, enabling real-time decision making and personalized healthcare delivery. This research paper explores the role of AI-based telemonitoring in chronic disease management, assessing its applications, benefits, and challenges. The study includes a detailed methodology based on patient data analytics, a case study on diabetic patients using AI-integrated wearable systems, and the results derived from patient questionnaires. The findings suggest that AI-enabled telemonitoring significantly improves patient outcomes, reduces hospital readmissions, and enhances adherence to treatment plans. The paper concludes that AI-driven telemonitoring can redefine chronic disease management, bridging the gap between patients and healthcare providers through precision, efficiency, and continuous engagement.