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dc.contributor.authorNimmagadda, Shastri
dc.contributor.authorNimmagadda, S.
dc.contributor.authorDreher, H.
dc.identifier.citationNimmagadda, 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.

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.

dc.titleMultidimensional data warehousing & mining of diabetes & food-domain ontologies for e-Health
dc.typeConference Paper
dcterms.source.titleIEEE International Conference on Industrial Informatics (INDIN)
dcterms.source.seriesIEEE International Conference on Industrial Informatics (INDIN)
curtin.departmentSchool of Information Systems
curtin.accessStatusFulltext not available

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