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The design and implementation of the elderly healthcare information mining platform

  • School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Global aging brings new challenges to elderly healthdata management. Existing systems such as HIS and CIS focus on the storage and management of information, the key limitations are that they lack effective mining approaches and usually cannot handle the large-scale health data, these drawbacks make them very hard to be a robust and light-weight system. In this paper, we develop a memory computing based elderly healthcare information mining platform. The platform can (1) provide memory computing based parallel storage and computing framework for complex and heterogeneous elderly health data; (2) implement a workflow to manage the data mining process; (3) provide a friendly operating interface. Extensive experiment on elderly heart disease dataset shows that the platform achieves high prediction accuracy and fast running time.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
EditorsIllhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1501-1506
Number of pages6
ISBN (Electronic)9781509030491
DOIs
StatePublished - 15 Dec 2017
Externally publishedYes
Event2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States
Duration: 13 Nov 201716 Nov 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume2017-January

Conference

Conference2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Country/TerritoryUnited States
CityKansas City
Period13/11/1716/11/17

Keywords

  • Data mining platform
  • Elderly health data analysis
  • Memory computing

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