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Application of data mining in medical domain: case of cardiology sickness level

Saraee, M, Waheed, A, Javed, S and Nigam, J 2005, Application of data mining in medical domain: case of cardiology sickness level , in: Mathematics and Engineering Techniques in Medicine and Biological Sciences (METMBS), 20-23 June 2005, Las Vegas.

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      Abstract

      This paper is concerned with the development of data mining tools in the domain of the medical field of heart diseases/attack. We carried out extensive experiments applying different data mining techniques including Classification, Association rules Mining and Clustering. We learned from experience the challenges for mining medical data. This will also indicate the differences with regards to performance based on the task of extracting data from a data set. The basic plan for this experiment is as follows, firstly the extracted medical data will have to be cleaned and arranged in a suitable format which is compatible with the Envisioner software which we are going to use to conduct the experiment in. Secondly relevance analysis will be carried to retrieve the most relevant attributes. Using those attributes the above tools the dataset will be mined. After conducting the experiment we can now state that Mining is a great tool for identifying trends but it has still a long way to go before complete diagnoses can be made.

      Item Type: Conference or Workshop Item (Paper)
      Themes: Health and Wellbeing
      Schools: Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering > Data Mining and Pattern Recognition Research Centre
      Journal or Publication Title: Proceedings of the 2005 International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences
      Publisher: Mathematics and Engineering Techniques in Medicine and Biological Sciences
      Refereed: Yes
      Related URLs:
      Depositing User: Dr Mo Saraee
      Date Deposited: 26 Oct 2011 10:29
      Last Modified: 20 Aug 2013 18:16
      URI: http://usir.salford.ac.uk/id/eprint/18655

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