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Real-time analysis of vital signs using incremental data stream mining techniques with a case study of ARDS under ICU treatment
Fong, Simon1; Siu, Shirley W. I.1; Zhou, Suzy2; Chan, Jonathan H.3; Mohammed, Sabah4; Fiaidhi, Jinan4
2015-09
Source PublicationJournal of Medical Imaging and Health Informatics
ISSN2156-7018
Volume5Issue:5Pages:1108-1115
Abstract

Analysing data streams of vital signs has been a popular topic in research communities with techniques mainly focusing on detection, classification and prediction. One drawback for data classification/prediction is that the data mining model is built based on a full set of stationary data. Updating the model for sustaining the classification accuracy often needs the whole dataset including the evolving data to be accessed. This nature of model rebuilding dampers the possibility of mining vital signs in real-time and at high speed. Unfortunately, much of the past papers in the literature were based on traditional data mining models. In this paper, a data stream mining model which is flexible in configuring with different incremental data stream learning methods is tested as a real-time classification engine for mining vital data streams. A computer simulation experiment is conducted that is based on a case study of adult respiratory distress syndrome under twelve-hours of ICU treatment. The results indicate promising possibilities of performing real-time prediction by the proposed model.

KeywordData Stream Mining Naïve Bayes Optimized Very Fast Decision Tree Support Vector Machine Vital Signs Analysis
DOIhttps://doi.org/10.1166/jmihi.2015.1504
URLView the original
Indexed BySCI
Language英语
WOS Research AreaMathematical & Computational Biology ; Radiology, Nuclear Medicine & Medical Imaging
WOS SubjectMathematical & Computational Biology ; Radiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000361271900032
PublisherAMER SCIENTIFIC PUBLISHERS, 26650 THE OLD RD, STE 208, VALENCIA, CA 91381-0751 USA
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Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Univ Macau, Dept Comp & Informat Sci, Macau Sar, Peoples R China
2.Mozat Pte Ltd, Dept Prod Management, Singapore 118256, Singapore
3.King Mongkuts Univ Technol Thonburi, Sch Informat Technol, Bangkok 10140, Thailand
4.Lakehead Univ, Dept Comp Sci, Thunder Bay, ON P7B 5E1, Canada
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Fong, Simon,Siu, Shirley W. I.,Zhou, Suzy,et al. Real-time analysis of vital signs using incremental data stream mining techniques with a case study of ARDS under ICU treatment[J]. Journal of Medical Imaging and Health Informatics,2015,5(5):1108-1115.
APA Fong, Simon,Siu, Shirley W. I.,Zhou, Suzy,Chan, Jonathan H.,Mohammed, Sabah,&Fiaidhi, Jinan.(2015).Real-time analysis of vital signs using incremental data stream mining techniques with a case study of ARDS under ICU treatment.Journal of Medical Imaging and Health Informatics,5(5),1108-1115.
MLA Fong, Simon,et al."Real-time analysis of vital signs using incremental data stream mining techniques with a case study of ARDS under ICU treatment".Journal of Medical Imaging and Health Informatics 5.5(2015):1108-1115.
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