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Medical Data Mining for Discovering Periodically Frequent Diseases from Transactional Databases

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Computational Intelligence in Data Mining - Volume 1

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 31))

Abstract

Medical data mining has witnessed significant progress in the recent past. It unearths the latent relationships among clinical attributes for finding interesting facts which helps experts in health care in decision making. Recently, frequent patterns in transactional medical databases that occur periodically are exploited to know the temporal aspects of various diseases. In this paper we modified K-means algorithm to extract yearly and monthly periodic frequent patterns from medical datasets. The datasets contain electronic health records of 2012 and 2013. Periodical frequent patterns between these years and monthly patterns were extracted using the proposed methodology. To achieve this we used the notion of making temporal view that is instrumental in adapting K-means for this purpose. We built a prototype to test the algorithm and the empirical results reveal that the proposed methodology for knowledge discovery related periodic frequent diseases is useful. The application can be reused to have lasting implications on health care industry for improving quality of services with strategic and expert decision making.

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Authors and Affiliations

  1. Sambalpur University, Orissa, India

    Mohammed Abdul Khaleel, G. N. Dash & K. S. Choudhury

  2. Utkal University, Orissa, India

    Mohiuddin Ali Khan

Authors
  1. Mohammed Abdul Khaleel
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  2. G. N. Dash
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  3. K. S. Choudhury
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  4. Mohiuddin Ali Khan
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Corresponding author

Correspondence to Mohammed Abdul Khaleel .

Editor information

Editors and Affiliations

  1. University of Canberra, Canberra, Australia and University of South Australia, Adelaide, South Australia, Australia

    Lakhmi C. Jain

  2. Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  4. Dept. of Computer Science and Engineering, National Institute of Technology Rourkela, Rourkela, India

    Durga Prasad Mohapatra

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Khaleel, M.A., Dash, G.N., Choudhury, K.S., Khan, M.A. (2015). Medical Data Mining for Discovering Periodically Frequent Diseases from Transactional Databases. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 1. Smart Innovation, Systems and Technologies, vol 31. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2205-7_9

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  • DOI: https://doi.org/10.1007/978-81-322-2205-7_9

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2204-0

  • Online ISBN: 978-81-322-2205-7

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