Welcome to the InfoSci Platform
Reference Hub7
Remote Health Patient Monitoring System for Early Detection of Heart Disease

Remote Health Patient Monitoring System for Early Detection of Heart Disease

Gokulnath Chandra Babu, Shantharajah S. P.
Copyright: © 2021 |Volume: 13 |Issue: 2 |Pages: 13
ISSN: 1938-0259|EISSN: 1938-0267|EISBN13: 9781799860174|DOI: 10.4018/IJGHPC.2021040107
Cite Article Cite Article

MLA

Babu, Gokulnath Chandra, and Shantharajah S. P. "Remote Health Patient Monitoring System for Early Detection of Heart Disease." IJGHPC vol.13, no.2 2021: pp.118-130. http://doi.org/10.4018/IJGHPC.2021040107

APA

Babu, G. C. & Shantharajah S. P. (2021). Remote Health Patient Monitoring System for Early Detection of Heart Disease. International Journal of Grid and High Performance Computing (IJGHPC), 13(2), 118-130. http://doi.org/10.4018/IJGHPC.2021040107

Chicago

Babu, Gokulnath Chandra, and Shantharajah S. P. "Remote Health Patient Monitoring System for Early Detection of Heart Disease," International Journal of Grid and High Performance Computing (IJGHPC) 13, no.2: 118-130. http://doi.org/10.4018/IJGHPC.2021040107

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

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.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.