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    Multidimensional data warehousing & mining of diabetes & food-domain ontologies for e-Health

    Access Status
    Fulltext not available
    Authors
    Nimmagadda, Shastri
    Nimmagadda, S.
    Dreher, H.
    Date
    2011
    Type
    Conference Paper
    
    Metadata
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    Citation
    Nimmagadda, S.L. and Nimmagadda, S.K. and Dreher, H. 2011. Multidimensional data warehousing & mining of diabetes & food-domain ontologies for e-Health, pp. 682-687.
    Source Title
    IEEE International Conference on Industrial Informatics (INDIN)
    DOI
    10.1109/INDIN.2011.6034973
    ISBN
    9781457704345
    School
    School of Information Systems
    URI
    http://hdl.handle.net/20.500.11937/31480
    Collection
    • Curtin Research Publications
    Abstract

    Authors propose a robust ontology based multidimensional data warehousing and mining approach to address the issues of organizing, reporting and documenting diabetes cases including causalities. Data mining procedures, in which map and data views depicting similarity and comparison of attributes extracted from warehouses, are used in the present studies, for understanding the ailments based on gender, age, geography, food habits and hereditary traits. Besides data visualization, data interpretation is proposed for full-bodied diagnosis, subsequent prescription and appropriate medication. This approach provides a robust back-end application for any web-based patient-doctor consultations and e-Health care management systems adopted by medical and social service providers. © 2011 IEEE.

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