Prediction of paediatric asthma hospitalisation using data mining techniques


Autoria(s): Schmidt, Sam; Li, Gang; Chen, Yi-Ping Phoebe
Contribuinte(s)

Chetty, Madhu

Ahmad, Shandar

Ngom, Alioune

Teng, Shyh Wei

Data(s)

01/01/2008

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

http://hdl.handle.net/10536/DRO/DU:30018159

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