Big Data Analysis for Aids Disease Detection System using Clustering Technique
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2017 by IJCTT Journal|
|Year of Publication : 2017|
|Authors : S. Packiyam, A. Prema|
|DOI : 10.14445/22312803/IJCTT-V48P118|
S. Packiyam, A. Prema "Big Data Analysis for Aids Disease Detection System using Clustering Technique". International Journal of Computer Trends and Technology (IJCTT) V48(2):85-92, June 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Big data analysis is the demanding one because it contains large amount of records. In today’s world, the massive information in health care is to be processed in order to recognize, diagnose, detect and prevent the various diseases. It is projected to develop a centralized patient monitoring system using big data. In the planned system, large set of medical records are full as input. From this medical data set, it is aimed to extract the required information from the record of AIDS patients using clustering technique. The classification process states whether the patient is normal or abnormal and in the detection step using clustering technique to detect the disease and decrease the dataset. Thus, the proposed system helps to classify a large and complex medical dataset and detect the AIDS disease. Hadoop is the most popular platform for big data analysis. The Hadoop ecosystem is vast and involves many supporting frameworks and tools to effectively run and manage it. This article focuses on the center of Hadoop concepts and its technique to handle data.
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Big data, Hadoop, Cluster, AIDS.