You are not logged in.

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, doi: 10.1007/978-3-540-85984-0.

Attached Files
Name Description MIMEType Size Downloads

Title Medical knowledge discovery from a regional asthma dataset
Author(s) Schmidt, Sam
Li, GangORCID iD for Li, Gang
Chen, Yi-Peng Phoebe
Journal name Lecture notes in computer science
Volume number 5227
Start page 888
End page 895
Total pages 8
Publisher Springer Berlin / Heidelberg
Place of publication Berlin, Germany
Publication date 2008
ISSN 0302-9743
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
DOI 10.1007/978-3-540-85984-0
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

Document type: Journal Article
Collection: School of Engineering and Information Technology
Connect to link resolver
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 635 Abstract Views, 2 File Downloads  -  Detailed Statistics
Created: Fri, 14 Aug 2009, 13:55:24 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact