Integrative visual data mining of biomedical data: Investigating cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia

Publication Type:
Visual Data Mining: Theory, Techniques and Tools for Visual Analytics, 2008, 1, pp. 367 - 388
Issue Date:
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2008001291.pdf713.65 kB
Adobe PDF
This chapter presents an integrative visual data mining approach towards biomedical data. This approach and supporting methodology are presented at a high level. They combine in a consistent manner a set of visualisation and data mining techniques that operate over an integrated data set of several diverse components, including medical (clinical) data, patient outcome and interview data, corresponding gene expression and SNP data, domain ontologies and health management data. The practical application of the methodology and the specific data mining techniques engaged are demonstrated on two case studies focused on the biological mechanisms of two different types of diseases: Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia, respectively. The common between the cases is the structure of the data sets.
Please use this identifier to cite or link to this item: