Medical knowledge discovery from a regional asthma dataset

Schmidt, Sam, Li, Gang and Chen, Yi-Peng Phoebe 2008, Medical knowledge discovery from a regional asthma dataset, Lecture notes in computer science, vol. 5227, pp. 888-895.

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Title Medical knowledge discovery from a regional asthma dataset
Author(s) Schmidt, Sam
Li, Gang
Chen, Yi-Peng Phoebe
Journal name Lecture notes in computer science
Volume number 5227
Start page 888
End page 895
Publisher Springer Berlin / Heidelberg
Place of publication Berlin, Germany
Publication date 2008
ISSN 0302-9743
1611-3349
Summary Paediatric asthma represents a significant public health problem. To date, clinical data sets have typically been examined using traditional data analysis techniques. While such traditional statistical methods are invariably widespread, large volumes of data may overwhelm such approaches. The new generation of knowledge discovery techniques may therefore be a more appropriate means of analysis. The primary purpose of this study was to investigate an asthma data set, with the application of various data mining techniques for knowledge discovery. The current study utilises data from an asthma data set (n ≈ 17000). The findings revealed a number of factors and patterns of interest.
Language eng
Field of Research 080301 Bioinformatics Software
HERDC Research category C1 Refereed article in a scholarly journal
HERDC collection year 2008
Copyright notice ©2008, Springer-Verlag Berlin Heidelberg
Persistent URL http://hdl.handle.net/10536/DRO/DU:30017627

Document type: Journal Article
Collection: School of Engineering and Information Technology
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