IoT-Enabled Predictive Analytics for Chronic Disease Management Using Machine Learning
Abstract
Effective management of chronic diseases requires continuous monitoring and timely interventions. This paper investigates the use of IoT-enabled predictive analytics for chronic disease management, focusing on conditions such as diabetes and hypertension. We develop a predictive model using machine learning algorithms to analyze data from IoT devices, predicting disease exacerbations and suggesting proactive measures. The system's efficacy is validated through a longitudinal study, demonstrating improved disease management and patient adherence to treatment plans. The paper also discusses the integration of predictive analytics into existing healthcare systems and the potential for scaling this approach.
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