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- W2910852004 abstract "Internet of things and machine learning has empowered smart health applications focused on healthcare sector, where, heart diseases are rapidly growing issue. Heart diseases are chronic diseases, where continuous monitoring is necessary. With the rising availability of personal healthcare devices, Internet of things can be applied to develop health monitoring systems. In the context of diagnosing this study focus on identifying optimum machine learning classifier among several different machine leaning classifiers for heart disease diagnosis and for the training and testing the machine learning models this study used UCI machine learning repository for Heart diseases. In the context of heart diseases monitoring this study focus on prototyping personal healthcare devices, use Bluetooth Low Energy for data transmission and development of iOS mobile application for integrating diagnosing and monitoring systems." @default.
- W2910852004 created "2019-01-25" @default.
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- W2910852004 date "2018-09-01" @default.
- W2910852004 modified "2023-10-13" @default.
- W2910852004 title "Approach to Heart Diseases Diagnosis and Monitoring through Machine Learning and iOS Mobile Application" @default.
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- W2910852004 doi "https://doi.org/10.1109/icter.2018.8615504" @default.
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