Integrating Machine Learning and IoT for Enhanced Patient Monitoring in Healthcare: A Comprehensive Review
Abstract
The integration of Machine Learning (ML) and Internet of Things (IoT) technologies is revolutionizing patient monitoring in healthcare. This paper presents a comprehensive review of the current advancements in applying ML algorithms to IoT-enabled healthcare systems. We explore various IoT devices used for continuous health monitoring, such as wearable sensors and smart medical equipment, and how ML techniques enhance data analysis, prediction, and decision-making. Key applications discussed include early detection of diseases, personalized treatment plans, and remote patient monitoring. We also address challenges such as data privacy, interoperability, and the need for real-time processing. Our findings highlight the potential of ML and IoT to improve patient outcomes, reduce healthcare costs, and enable proactive healthcare management.
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