Prediction of paediatric asthma hospitalisation using data mining techniques
Contribuinte(s) |
Chetty, Madhu Ahmad, Shandar Ngom, Alioune Teng, Shyh Wei |
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Data(s) |
01/01/2008
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Resumo |
Research into the prevalence of hospitalisation among childhood asthma cases is undertaken, using a data set local to the Barwon region of Victoria. Participants were the parents/guardians on behalf of children aged between 5-11 years. Various data mining techniques are used, including segmentation, association and classification to assist in predicting and exploring the instances of childhood hospitalisation due to asthma. Results from this study indicate that children in inner city and metropolitan areas may overutilise emergency department services. In addition, this study found that the prediction of hospitalisaion for asthma in children was greater for those with a written asthma management plan.<br /> |
Identificador | |
Idioma(s) |
eng |
Publicador |
Springer Berlin / Heidelberg |
Relação |
http://dro.deakin.edu.au/eserv/DU:30018159/li-predictionofpaediatric-2008.pdf http://www.infotech.monash.edu.au/about/news/conferences/prib08/ |
Tipo |
Conference Paper |