Research Article Open Access

Empirical Study on Applications of Data Mining Techniques in Healthcare

Harleen Kaur1 and Siri Krishan Wasan2
  • 1 ,
  • 2 , Afganistan
Journal of Computer Science
Volume 2 No. 2, 2006, 194-200

DOI: https://doi.org/10.3844/jcssp.2006.194.200

Submitted On: 3 September 2005 Published On: 28 February 2006

How to Cite: Kaur, H. & Wasan, S. K. (2006). Empirical Study on Applications of Data Mining Techniques in Healthcare. Journal of Computer Science, 2(2), 194-200. https://doi.org/10.3844/jcssp.2006.194.200

Abstract

The healthcare environment is generally perceived as being ‘information rich’ yet ‘knowledge poor’. There is a wealth of data available within the healthcare systems. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. Knowledge discovery and data mining have found numerous applications in business and scientific domain. Valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, we briefly examine the potential use of classification based data mining techniques such as Rule based, decision tree and Artificial Neural Network to massive volume of healthcare data. In particular we consider a case study using classification techniques on a medical data set of diabetic patients.

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Keywords

  • Healthcare
  • health data
  • medical diagnosis
  • data mining
  • artificial neural network
  • knowledge discovery in databases (KDD)