A Comprehensive and Experimental Survey on Medical Data Classification and Pattern Recognition

Authors

  • R. Subathra Devi  Research Scholar, PG and Research Department of Computer Science,Presidency College, Chennaii, Tamil Nadu, India

Keywords:

Medical support system, clinical support system, medical data classification, supervised classification, un-supervised classification, rule-based classification, DCT ,Bayesian classification, PNN artificial neural network adaptive classifier, K-NN, K-means, machine learning, svm, abdominal diseases.

Abstract

This paper is proposed to compare and analyze various type of medical data classification and pattern recognition methods. Medical data classification methods majorly divided into three categories such as supervised, classification and also semi-supervised classification. Pattern recognition and data classifications are both overlapped domain for useful knowledge generation and prediction from training data. The field of medical diagnosis (or) clinical support system needs in intelligent data classification and pattern recognition algorithms for more accuracy in clinical decision making. Supervised classification contains many methods such as rule based classification, decision tree based classification, Bayesian classification, KNN probabilistic neural network, SVM and more, combination of supervised classification called as ensemble algorithm. These types of mixed algorithm provide more accuracy. Unsupervised classification called lazy learner (or) clustering for example automatic classification of unlabeled data. Unsupervised classification also contains some types such as K-means, deep learning methods, hierarchical clustering and more. In this paper we have to analyze various types of classification algorithms using sample medical record of upper abdomen diseases database. In this paper we have to analyze maximum of algorithms in experimental using same training data, this will used for various performance and accuracy analysis.

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International Journal of Scientific Research in Science, Engineering and Technology

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2018-04-30

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Volume 4, Issue 4, March-April-2018

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[1]
R. Subathra Devi, " A Comprehensive and Experimental Survey on Medical Data Classification and Pattern Recognition, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 4, pp.1521-1537, March-April-2018.