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- W3200751323 abstract "Tuberculosis is one of the most prevalent diseases, which is a threat to the lives of many South Africans. The disease has been spreading at a high rate in the past years. World health organization reported that South Africa is amongst 22 countries most burdened by the disease that has around 80% of the total global Tuberculosis cases. Despite the fact that the South African government is undertaking Tuberculosis campaigns, there is still a challenge in the control of the spread of Tuberculosis. The lack of awareness and access to information further contributes to the high rate at which Tuberculosis is spreading. Therefore, we developed a decision support system for Tuberculosis prevalence in South Africa. We used Bayesian network to aggregate, analyse and mine data received from health department of Mpumalanga province. The data is stored in MySQL database. We used WampServer environment, which enabled us to develop a web application. The proposed model educates, informs, and prescribes measures to take when visiting a high prevalence location. We then tested the system developed with data from Mpumalanga provincial health department showing that males are more at risk with prevalence rate of 53%, 0–35 age group are the most affected at 50%, Ehlanzeni location in Mpumalanga province is the most affected at 47%, pulmonary Tuberculosis is the most prevalence at 90% and the survival rate is at 87%. We evaluated the model achieving a utility of 88.2%. We believe this utility can be improved with more training and accurate data." @default.
- W3200751323 created "2021-09-27" @default.
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- W3200751323 date "2021-01-01" @default.
- W3200751323 modified "2023-09-25" @default.
- W3200751323 title "A Decision Support System for Tuberculosis Prevalence in South Africa" @default.
- W3200751323 cites W2027978905 @default.
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- W3200751323 doi "https://doi.org/10.1007/978-3-030-86973-1_19" @default.
- W3200751323 hasPublicationYear "2021" @default.
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