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title

A REVIEW PAPER ON DENGUE DISEASE FORCASTING USING DATA MINING TECHNIQUES

Author(s):

Vandana Rajput

Keywords:

Data Mining, Dengue Fever & its Virus, Association Rule Mining(ARM), ARM Algorithms: Apriori, FP-Growth and so on.

Abstract

Data Mining is a standout amongst the most comprehensively and rousing zones of research with the motivation behind discovering significant information from vast data collections In Medical ventures, Data Mining gives many points of interest, for example, the location of the extortion in medical coverage, illness forecast, and accessibility of the therapeutic solution for the patients at lower cost, recognition of reasons for sicknesses and distinguishing proof of restorative treatment techniques. It is additionally helpful to foresee the hazardous maladies like-Dengue fever, Cancer, Diabetes and so forth. In this paper, we have learned about data mining that is utilized as a part of the restorative information field. There are different issues in getting information since data are put away in various – diverse arrangement which is profoundly intricate. We depict a dengue fever forecast. Forecasts (or Prediction) are most critical things to foresee the infections on the premise of manifestations, topographical illustrations area, and others. Dengue fever is an influenza-like an infection that happens by the chomp of Aedes mosquitoes which is quick developing as a noteworthy medical issue. In this study, we characterize dengue fever, its infections, and indications. Here, we likewise characterize the association rule mining that has diverse distinctive algorithms which are additionally helpful in prediction.

Other Details

Paper ID: IJSARTV
Published in: Volume : 3, Issue : 4
Publication Date: 4/1/2017

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