Iot-Enabled Predictive Analytics for Hypertension and Cardiovascular Disease

Abstract

The recent studies have highlighted the transformative potential of the convergence of Internet of Things (IoT) technologies and predictive analytics into the healthcare systems, especially in the early diagnosis and treatment of hypertension and cardiovascular diseases (CVD). The paper analyzes how IoT-based predictive analytics has contributed to cardiovascular health by monitoring in real-time and providing insights using data. Using IoT devices (wearables, biosensors, and interconnected medical equipment), clinicians have access to continuous streams of patient data and these streams are assessed with machine learning (ML) and artificial intelligence (AI) algorithms. Such innovative technologies will help to predict risks accurately, allow implementing preventive measures, and adopt personalized treatment plans, which will reduce the impact of cardiac disease on the patient population and hospital facilities. The review covers several frameworks of the IoT, predictive models, and real-time monitoring systems, and their application in the development of preventive medicine. Besides, it focuses on the issues of data privacy, security, and the incorporation of the IoT systems into the current healthcare facilities. The paper will finally end with a provocative indication of the future course of the IoT-enabled healthcare analytics and how the notion of synergy with cloud computing and edge intelligence can be adopted to achieve even better patient outcomes and system optimization.