Multidimensional data warehousing & mining of diabetes & food-domain ontologies for e-Health
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 ext...
| Main Authors: | , , |
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| Format: | Conference Paper |
| Published: |
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/31480 |
| _version_ | 1848753392254451712 |
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| author | Nimmagadda, Shastri Nimmagadda, S. Dreher, H. |
| author_facet | Nimmagadda, Shastri Nimmagadda, S. Dreher, H. |
| author_sort | Nimmagadda, Shastri |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T08:23:47Z |
| format | Conference Paper |
| id | curtin-20.500.11937-31480 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:23:47Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-314802017-09-13T15:19:08Z Multidimensional data warehousing & mining of diabetes & food-domain ontologies for e-Health Nimmagadda, Shastri Nimmagadda, S. Dreher, H. 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. 2011 Conference Paper http://hdl.handle.net/20.500.11937/31480 10.1109/INDIN.2011.6034973 restricted |
| spellingShingle | Nimmagadda, Shastri Nimmagadda, S. Dreher, H. Multidimensional data warehousing & mining of diabetes & food-domain ontologies for e-Health |
| title | Multidimensional data warehousing & mining of diabetes & food-domain ontologies for e-Health |
| title_full | Multidimensional data warehousing & mining of diabetes & food-domain ontologies for e-Health |
| title_fullStr | Multidimensional data warehousing & mining of diabetes & food-domain ontologies for e-Health |
| title_full_unstemmed | Multidimensional data warehousing & mining of diabetes & food-domain ontologies for e-Health |
| title_short | Multidimensional data warehousing & mining of diabetes & food-domain ontologies for e-Health |
| title_sort | multidimensional data warehousing & mining of diabetes & food-domain ontologies for e-health |
| url | http://hdl.handle.net/20.500.11937/31480 |