AI for Remote Patient Monitoring: Bridging the Gap in Chronic Disease Management
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Abstract
The rise of wearable devices and IoT-enabled healthcare technologies has paved the way for AI-powered remote patient monitoring systems. This paper investigates the use of machine learning algorithms in analyzing continuous health data streams to manage chronic conditions such as diabetes, heart disease, and COPD. Examples include predictive models for early intervention, anomaly detection, and personalized health recommendations. The paper also examines barriers such as data security, patient compliance, and interoperability with existing healthcare systems.
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AI for Remote Patient Monitoring: Bridging the Gap in Chronic Disease Management. (2020). International Machine Learning Journal and Computer Engineering, 3(3). https://mljce.in/index.php/Imljce/article/view/44
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Articles
How to Cite
AI for Remote Patient Monitoring: Bridging the Gap in Chronic Disease Management. (2020). International Machine Learning Journal and Computer Engineering, 3(3). https://mljce.in/index.php/Imljce/article/view/44