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Critical Analysis of Data Mining Techniques on Medical Data
Author(s) -
Zahid Ullah,
Muhamma Fayaz,
Asif Iqbal
Publication year - 2016
Publication title -
international journal of modern education and computer science
Language(s) - English
Resource type - Journals
eISSN - 2075-017X
pISSN - 2075-0161
DOI - 10.5815/ijmecs.2016.02.05
Subject(s) - computer science , data mining , decision tree , cluster analysis , association rule learning , decision tree learning , identification (biology) , machine learning , botany , biology
The use of Data mining techniques on medical data is dramatically soar for determining helpful things which are used in decision making and identification. The most extensive data mining techniques which are used in healthcare domain are, classification, clustering, regression, association rule mining, classification and regression tree (CART). The suitable use of data mining algorithm can enhance the quality of prediction, diagnosis and disease classification. Valuation of data mining techniques demand for medical data mining is the major goal here, particularly to examine the local frequent disease like heart ailments, breast cancer, lung cancer and so on. We examine for discovering the locally frequent patterns through data mining technique in terms of cost performance speed and accuracy.

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