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    Ontology based data warehouse modeling and managing ecology of human body for disease and drug prescription management

    20619_downloaded_stream_75.pdf (972.2Kb)
    Access Status
    Open access
    Authors
    Nimmagadda, Shastri
    Nimmagadda, Sashi
    Dreher, Heinz
    Date
    2008
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Nimmagadda, Shastri L. and Nimmagadda, Sashi K. and Dreher, Heinz. 2008. : Ontology based data warehouse modeling and managing ecology of human body for disease and drug prescription management, in Chang, Elizabeth and Hussain, Farookh Khadeer (ed), Digital Ecosystems and Technologies, 2008. DEST 2008. 2nd IEEE International Conference on, 26 Feb 2008, pp. 212-220. Phitsanulok, Thailand: IEEE.
    Source Title
    Digital Ecosystems and Technologies, 2008. DEST 2008. 2nd IEEE International Conference on
    Source Conference
    Digital Ecosystems and Technologies, 2008. DEST 2008. 2nd IEEE International Conference on
    DOI
    10.1109/DEST.2008.4635209
    Faculty
    Curtin Business School
    School of Information Systems
    URI
    http://hdl.handle.net/20.500.11937/39582
    Collection
    • Curtin Research Publications
    Abstract

    Health care sector is currently experiencing a major crisis with information overload. With the increasing prevalence of chronic diseases and the ageing population the amount of paper-work is more than ever before. In the US, a hospital admission of one patient generates an estimate of 60 pieces of paper. The federal governments of various countries have passed policies and initiatives that focus on introducing information systems into the health care sector. Technology will immensely reduce the cost of managing patients and even reduce the risks of mis-diagnosing and prescribing incorrectmedications to patients. This paper primarily focuses on introducing the concept of ontology based warehouse modelling and managing ecology of human body for disease and drug prescription management. Disorders of the human body and factors such as the patient?s age, living and working conditions, familial and genetic influences can be simulated into Metadata in a warehousing environment. In this environment, various relationships are identified and described between these factors and the diseases. Secondly, we also introduce ontological representation of the various human body systems such as the digestive, musculoskeletal and nervous system in disease processes. Although this is an extensive and complex knowledge domain, the work in this paper is one of the first to attempt to introduce the use of ontology based data warehousing and data mining conceptually. We also aim at implementing and applying this research in practice.

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