A new approach to IoT-based disease diagnosis using genetic algorithms and various classifiers
Subject Areas : Special
seyed ebrahim
dashti
1
(Assistant Professor, Faculty of Electrical and Computer Engineering, Jahrom Branch, Islamic Azad University, Jahrom, Fars, Iran)
maryam
nikpor
2
(PhD student, Faculty of Electrical and Computer Engineering, Islamic Azad University, Fars, Iran)
mehdi
nikpor
3
(Instructor, Bandar Abbas University of Medical Sciences, Hormozgan, Iran)
mahbobe
johari
4
(Master's degree, Fasa Islamic Azad University, Fars, Iran)
Keywords: Smart health, machine learning, Internet of Things (IoT), Ensemble learning, diabetes,
Abstract :
Medical information technology and health services are related to the national welfare and livelihood of the people. The integration of cloud computing and the Internet of Things will be a major breakthrough in modern medical applications. This study focuses on the chronic disease of diabetes, which is one of the leading causes of death worldwide. This research has applied medical information technology in the field of IoT, especially in the field of medical monitoring and management applications. A model architecture for remote monitoring and management of the health information cloud platform is proposed and analyzed, and then an algorithm based on genetic algorithm and hybrid classification for the diagnosis of diabetes is proposed for medical monitoring. The results show that the proposed method has a higher performance than the basic methods and has reached an accuracy of 94%.
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