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)
| dc.contributor.advisor | Rama, Bandaru (PhD) | |
| dc.contributor.author | Tesso, Aberham | |
| dc.date.accessioned | 2020-05-26T10:07:19Z | |
| dc.date.accessioned | 2023-11-18T12:44:44Z | |
| dc.date.available | 2020-05-26T10:07:19Z | |
| dc.date.available | 2023-11-18T12:44:44Z | |
| dc.date.issued | 2005-06 | |
| dc.description.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. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/12345678/21311 | |
| dc.language.iso | en | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Technology to Identify Determinant Risk | en_US |
| dc.title | 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) | en_US |
| dc.type | Thesis | en_US |