A Survey on Various Disease Prediction Techniques
Journal: International Journal of Trend in Scientific Research and Development (Vol.2, No. 6)Publication Date: 19/11/2018
Authors : C. Leancy Jannet G. V. Sumalatha;
Page : 734-737
Keywords : Bioinformatics; Prediction; Genes; Data Mining; Text Mining; Hyper triglyceride mi a; Missing Values; Hmv and Classifiers;
Abstract
An analysis of various diseases have been predicted using multiple data mining and text mining techniques. In this article we are going to discuss about 6 prediction techniques. Using gene expression pattern we predict the disease outcome and implementation of pathway based approach for classifying disease based on hyper box principles, we also present a novel hybrid prediction model with missing value imputation HPM-MI which analyze imputation using simple k-means clustering. A technique based on CCAR Constraint Class Association Rule has been used for reducing time consumption in prediction of a particular disease. We have discussed about text mining technique and their applications. Another technique has also been studied about hyper triglyceride mia from anthropometric measures which diverge according to age and gender. Using multilayer classifiers for disease prediction we can achieve high diagnosis accuracy and high performance. C. Leancy Jannet | G. V. Sumalatha "A Survey on Various Disease Prediction Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18624.pdf
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Last modified: 2018-11-19 19:34:39