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Integrative Visual Data Mining of Biomedical Data: Investigating Cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia

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Visual Data Mining

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4404))

Abstract

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.

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Authors and Affiliations

  1. School of Computing and Mathematics, University of Western Sydney, NSW 2007, Australia

    Simeon J. Simoff

  2. Faculty of Information Technology, University of Technology, Sydney, PO Box 123, Broadway, NSW 2007, Australia

    Paul Kennedy, Simeon J. Simoff, Daniel R. Catchpoole, Franco Ubaudi & Ahmad Al-Oqaily

  3. The Oncology Research Unit, The Children’s Hospital at Westmead, Locked Bag 4001, Westmead, NSW 2145, Australia

    Daniel R. Catchpoole

  4. School of Computing, Queen’s University, Kingston, Canada

    David B. Skillicorn

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  1. Paul Kennedy
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  2. Simeon J. Simoff
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  3. Daniel R. Catchpoole
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  4. David B. Skillicorn
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  5. Franco Ubaudi
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  6. Ahmad Al-Oqaily
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Simeon J. Simoff Michael H. Böhlen Arturas Mazeika

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© 2008 Springer-Verlag Berlin Heidelberg

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Kennedy, P., Simoff, S.J., Catchpoole, D.R., Skillicorn, D.B., Ubaudi, F., Al-Oqaily, A. (2008). Integrative Visual Data Mining of Biomedical Data: Investigating Cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia. In: Simoff, S.J., Böhlen, M.H., Mazeika, A. (eds) Visual Data Mining. Lecture Notes in Computer Science, vol 4404. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71080-6_21

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  • DOI: https://doi.org/10.1007/978-3-540-71080-6_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71079-0

  • Online ISBN: 978-3-540-71080-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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