Date of Award
2009
Document Type
Thesis
Publisher
Edith Cowan University
Degree Name
Bachelor of Computer Science Honours
School
School of Computer and Information Science
Faculty
Faculty of Computing, Health and Science
First Supervisor
Chiou Peng Lam
Abstract
Data mining techniques have been used widely in many areas such as business, science, engineering and more recently in clinical medicine. These techniques allow an enormous amount of high dimensional data to be analysed for extraction of interesting information as well as the construction of models for prediction. One of the foci in health related research is Alzheimer's disease which is currently a non-curable disease where diagnosis can only be confirmed after death via an autopsy. Using multi-dimensional data and the applications of data mining techniques, researchers hope to find biomarkers that will diagnose Alzheimer's disease as early as possible. The primary purpose of this research project is to investigate the application of data mining techniques for finding interesting biomarkers from a set of Alzheimer's disease related data. The findings from this project will help to analyse the data more effectively and contribute to methods of providing earlier diagnosis of the disease.
Recommended Citation
Dang, V. Q. (2009). Investigating data mining techniques for extracting information from Alzheimer's disease data. Edith Cowan University. https://ro.ecu.edu.au/theses_hons/1422