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  • 标题:Survey on Prediction of Heart Morbidity Using Data Mining Techniques
  • 本地全文:下载
  • 作者:K.Srinivas ; G.Raghavendra Rao ; A.Govardhan
  • 期刊名称:International Journal of Data Mining & Knowledge Management Process
  • 印刷版ISSN:2231-007X
  • 电子版ISSN:2230-9608
  • 出版年度:2011
  • 卷号:1
  • 期号:3
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:Data mining is the non trivial extraction of implicit, previously unknown and potentially useful information from data. Data mining technology provides a user- oriented approach to novel and hidden patterns in the data. This paper presents about the various existing techniques, the issues and challenges associated with them. The discovered knowledge can be used by the healthcare administrators to improve the quality of service and also used by the medical practitioners to reduce the number of adverse drug effect, to suggest less expensive therapeutically equivalent alternatives. In this paper we discuss the popular data mining techniques namely, Decision Trees, Naïve Bayes and Neural Network that are used for prediction of disease.
  • 关键词:KDD; data mining; machine learning algorithms; classifiers; disease prediction; time series; ARIMA;DSDM.
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