期刊
INTERNATIONAL JOURNAL OF GRID AND HIGH PERFORMANCE COMPUTING
卷 13, 期 2, 页码 118-130出版社
IGI GLOBAL
DOI: 10.4018/IJGHPC.2021040107
关键词
Apache Mahout; Healthcare; Internet of Things; Machine Learning; ROC Curve; Sensors
This paper introduces a heart disease prediction model utilizing IoT-enabled healthcare to collect and analyze a large volume of medical data through a three-step process, concluding with the use of ROC curve to identify parameters leading to heart disease.
This paper presents a heart disease prediction model. Among the recent technology, internet of things-enabled healthcare plays a vital role. The medical sensors used in healthcare provide a huge volume of medical data in a continuous manner. The speed of data generation in IoT healthcare is high so the volume of data is also high. In order to overcome this problem, the proposed model is a novel three-step process to store and analyze the large volumes of data. The first step focuses on a collection of data from sensor devices. In Step 2, HBase has been used to store the large volume of medical sensor data from a wearable device to the cloud. Step 3 uses Mahout for devolving logistic regression-based prediction model. At last, ROC curve is used to find the parameters that cause heart disease.
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