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Comparative research of swam intelligence clustering algorithms for analyzing medical data
XUEYUAN GONG1; LIANSHENG LIU2; SIMON FONG1; QIWEN XU1; TINGXI WEN3; ZHIHUA LIU3
2019-05-16
Source PublicationIEEE Access
ISSN2169-3536
Volume7Pages:137560-137569
Abstract

As the Internet of medical Things emerge in the field of medicine, the volume of medical data is expanding rapidly and along with its variety. As such, clustering is an important procedure to mine the vast data. Many swarm intelligence clustering algorithms, such as the particle swarm optimization (PSO), firefly, cuckoo, and bat, have been designed, which can be parallelized to the benefit of mass data computation. However, few studies focus on the systematic analysis of the time complexities, the effect of instances (data size), attributes (dimensionality), number of clusters, and agents of these algorithms. In this paper, we performed a comparative research for the PSO, firefly, cuckoo, and bat algorithms based on both synthetic and real medical data sets. Finally, we conclude which algorithms are effective for the medical data mining. In addition, we recommend the more suitable algorithms that have been developed recently for the different medical data to achieve the optimal clustering.

KeywordMedical Data Analysis Data Mining Swarm Intelligence Clustering Algorithms
DOI10.1109/ACCESS.2018.2881020
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000498710400008
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Scopus ID2-s2.0-85077812431
Fulltext Access
Citation statistics
Cited Times [WOS]:4   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorSIMON FONG
Affiliation1.Department of Computer and Information Science,Faculty of Science and Technology,University of Macau,Macao
2.First Affiliated Hospital,Guangzhou University of Traditional Chinese Medicine,Guangzhou,510405,China
3.Chinese Academy of Sciences,Shenzhen Institutes of Advanced Technology,Shenzhen,518055,China
First Author AffilicationFaculty of Science and Technology
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
XUEYUAN GONG,LIANSHENG LIU,SIMON FONG,et al. Comparative research of swam intelligence clustering algorithms for analyzing medical data[J]. IEEE Access,2019,7:137560-137569.
APA XUEYUAN GONG,LIANSHENG LIU,SIMON FONG,QIWEN XU,TINGXI WEN,&ZHIHUA LIU.(2019).Comparative research of swam intelligence clustering algorithms for analyzing medical data.IEEE Access,7,137560-137569.
MLA XUEYUAN GONG,et al."Comparative research of swam intelligence clustering algorithms for analyzing medical data".IEEE Access 7(2019):137560-137569.
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