By Topic

Research and Implementation of Massive Health Care Data Management and Analysis Based on Hadoop

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Hongyong Yu ; State Key Lab. of Software Archit., Neusoft Corp., Shenyang, China ; Deshuai Wang

New generation of health care IT systems are collecting and storing more and more data of patients. Useful knowledge can be extracted from the data in EMR or PHR to provide medical advises to patients, while through data analysis the result statistics can be used to support the scientific research. However, RDBMSs-based framework is not able to support the requirements of massive health care data storage, management and analysis. To solve the problem, this paper proposes a massive data management and analysis solution based on Hadoop to archive better performance, scalability and fault tolerance. The data management framework is presented. Besides, 2 different data analysis methods based on MapReduce and Hive are proposed. Experiment results of data upload, data query and data analysis show that the performance of the proposed framework is greatly improved, and a brief summary of the performance and the differences between 2 methods of MapReduce and Hive is also discussed.

Published in:

Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on

Date of Conference:

17-19 Aug. 2012