Data Mining, Soft Computing, Machine Learning and BioInspired Computing for Heart Disease Classification/ Prediction – A Review

  title={Data Mining, Soft Computing, Machine Learning and BioInspired Computing for Heart Disease Classification/ Prediction – A Review},
  author={M. Rathi and B. Narasimhan},
Data mining is the most common research area in the field of computer science and allied areas. Decision making in clinical data mining plays a significant role in patient’s life. In this survey research article we aim to portray various data mining algorithms, soft computing techniques, machine learning algorithms and bio-inspired algorithms for predicting / classifying heart disease. Several mechanisms namely apriori algorithm, frequent itemset mining, support vector machine, neural network… Expand
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  • Biology
  • 2014 International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE)
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  • Computer Science, Engineering
  • 2010 International Conference on Distributed Frameworks for Multimedia Applications
  • 2010
A Kohonen artificial neural network is presented as a model of DSS for the prediction of risk factor based coronary artery disease (CAD) and was successfully implemented and tested success rate of 89.47%. Expand
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  • 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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