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)
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Date
2005-06
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Addis Ababa University
Abstract
Nowadays, people all over the world have been challenged with the confronting
problem of HI VI A IDS . There is large scale of HIV-related data available at VCT
centers and other clinics and hospitals . What is demanding is knowledge from the
data that may help HIVI Also prevention activities.
This paper reports on the finding s of a research that had the objective to apply data
mining technology to find determinant risk factors of HIV infection and their
association rules, that would broaden the insight about HIVIAIDS. The study focused
on using VCT for the reason that the data availability in electronic format. A data set
of 5267 visitors is used.
In this paper the process of knowledge discovery and data mining functions are
described. Differ negativities are performed for the purpose of data preprocessing
using Ms Excel. Among the total records 70 % is use d to train the model and 30% is
used to validate classifier with unseen data. The Knowledge Stool (to identify the
factors) and WEKA (to mine their association rules) software’s are used for
experimenting the research.
In general, the research has re salted in determining the fro niter risk factors ,
analyzing the influence of each wit h decision tree and assessing their affinity. The
reported fin clings are promising, making the result usable to the health professional,
Gove ornament, policy makers, and the Society at large. And the whole research
process can be a good input for further research.
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Keywords
Technology to Identify Determinant Risk