Application Of Data Mining Technology To Identify Determinant Risk Factors Of Hiv Infection And To Find Their Association Rules The Case Of Center For Disease Control And Prevention (cdc)

Nowadays, people all over the world have been challenged with the confrontingrnproblem of HI VI A IDS . There is large scale of HIV-related data available at VCTrncenters and other clinics and hospitals . What is demanding is knowledge from therndata that may help HIVI Also prevention activities.rnThis paper reports on the finding s of a research that had the objective to apply datarnmining technology to find determinant risk factors of HIV infection and theirrnassociation rules, that would broaden the insight about HIVIAIDS. The study focusedrnon using VCT for the reason that the data availability in electronic format. A data setrnof 5267 visitors is used.rnIn this paper the process of knowledge discovery and data mining functions arerndescribed. Differ negativities are performed for the purpose of data preprocessingrnusing Ms Excel. Among the total records 70 % is use d to train the model and 30% isrnused to validate classifier with unseen data. The Knowledge Stool (to identify thernfactors) and WEKA (to mine their association rules) software’s are used forrnexperimenting the research.rnIn general, the research has re salted in determining the fro niter risk factors ,rnanalyzing the influence of each wit h decision tree and assessing their affinity. Thernreported fin clings are promising, making the result usable to the health professional,rnGove ornament, policy makers, and the Society at large. And the whole researchrnprocess can be a good input for further research.

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