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Mining Medical Data: Bridging the Knowledge Divide
Sam Schmidt, Peter Vuillermin, Bernard Jenner, Yongli Ren, Gang Li and Yi-Ping Phoebe Chen (2008). Mining Medical Data: Bridging the Knowledge Divide. In: , Proceedings of eResearch Australasia 2008. eResearch Australasia 2008, Melbourne, Australia, (). 28 September - 3 October 2008.
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| Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials) |
| Name |
Description |
MIMEType |
Size |
Downloads |
era08_54.pdf
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Conference paper |
application/pdf |
278.62KB |
238 |
| Author(s) |
Sam Schmidt
Peter Vuillermin
Bernard Jenner
Yongli Ren
Gang Li
Yi-Ping Phoebe Chen
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| Title of paper |
Mining Medical Data: Bridging the Knowledge Divide
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| Conference name |
eResearch Australasia 2008
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| Conference location |
Melbourne, Australia
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| Conference dates |
28 September - 3 October 2008
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| Convener |
Australian Department of Innovation, Industry, Science and Research
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| Proceedings title |
Proceedings of eResearch Australasia 2008
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| Publication date |
2008
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| Abstract/Summary |
Due to the signi¯cant amount of data generated by modern medicine there is a growing reliance on tools such as data mining and knowledge discovery to help make sense and comprehend such data. The success of this process requires collaboration and interaction between such methods and medical professionals. Therefore an important question is: How can we strengthen the relationship between two traditionally separate fields (technology and medicine) in order to work simultaneously towards enhancing knowledge in modern medicine. To address this question, this study examines the application of data mining techniques to a large asthma medical dataset. A discussion introducing various methods for a smooth approach, straying from the `jack of all trades, master of none' to a modular cooperative approach for a successful outcome is pro-posed. The results of this study support the use of data mining as a useful tool and highlight the advantages on a global scale of closer relations between the two distinct fields. The exploration of CRISP methodology suggests that a `one methodology fits all approach' is not appropriate, but rather combines to create a hybrid holistic approach to data mining.
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| Subjects |
280000 Information, Computing and Communication Sciences
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