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Approach to Heart Diseases Diagnosis and Monitoring through Machine Learning and iOS Mobile Application

机译:通过机器学习和iOS移动应用程序进行心脏病诊断和监控的方法

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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.
机译:物联网和机器学习已使专注于医疗保健领域的智能健康应用程序得到了应用,在该领域中,心脏病正迅速成为人们日益关注的问题。心脏病是慢性疾病,需要持续监测。随着个人医疗设备的可用性不断提高,物联网可以用于开发健康监控系统。在诊断本研究的背景下,本研究重点是在几种不同的机器学习分类器中确定最佳的机器学习分类器,以进行心脏病诊断以及训练和测试机器学习模型,该研究使用了针对心脏病的UCI机器学习存储库。在心脏病监测的背景下,本研究侧重于个人医疗设备的原型制作,使用低功耗蓝牙技术进行数据传输,并开发iOS移动应用程序以集成诊断和监测系统。

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