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Integrating Machine Learning, Artificial Intelligence, Deep Learning, and IoT in Remote Patient Monitoring
Abstract
The internet of things (IoT) can effectively manage remote patient healthcare monitoring systems, particularly in predicting chronic kidney disease levels. When IoT devices collect patient data, they transmit this information to a software platform that can be accessed by healthcare professionals or patients themselves. The healthcare industry, one of the largest globally, is experiencing significant changes due to the introduction of IoT. Many healthcare organizations are making substantial investments to transform their services and leverage the advantages of IoT, which has led to the development of the internet of medical things (IoMT), a network of medical sensors and supporting infrastructure. IoMT offers numerous benefits, such as enabling remote healthcare by monitoring patients' health from a distance, providing medical care to elderly individuals, and tracking the health status of large populations to detect and prevent epidemics.
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