Wilbert Sibanda

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This paper presents an application of Multi-layer Perceptrons (MLP) neural networks to model the demographic characteristics of antenatal clinic attendees in South Africa. The method of cross-validation is used to examine the between-sample variation of neural networks for HIV prediction. MLP neural networks for classifying both the HIV negative and(More)
In this study, a Central Composite Face Centered (CCF) design was employed to study the individual and interaction effects of demographic characteristics on the spread of HIV in South Africa. The demographic characteristics studied for each pregnant mother attending an antenatal clinic in South Africa, were mother's age, partner's age, mother's level of(More)
In this study, a Box Behnken Design (BBD) and a Binary Logistic Regression (BLR) were applied to study the effects of demographic characteristics on the risk of HIV in South Africa. The demographic characteristics studied for each pregnant mother attending an antenatal clinic in South Africa, were mother's age, partner's age (father's age), mother's level(More)
In this study, Central composite face-centered and Box–Behnken designs were employed to study the main and interaction effects of demographic characteristics on the risk of HIV in South Africa. The demographic characteristics studied for each pregnant mother attending an antenatal clinic in South Africa were mother’s age, partner’s age (father’s age),(More)
Neural networks have been applied successfully to a broad range of fields such as finance, data mining, medicine, engineering, geology, physics and biology. In finance, neural networks have been used for stock market prediction, credit rating, bankruptcy prediction and economic indicator forecasts. In medicine, neural networks have been used extensively in(More)
This research paper covers the development of an HIV risk scorecard using SAS Enterprise Miner#8482;. The HIV risk scorecard was developed using the 2007 South African annual antenatal HIV and syphilis seroprevalence data. Antenatal data contains various demographic characteristics for each pregnant woman, such as pregnant woman's age, male sexual partner's(More)
This paper presents an application of Multi-layer Perceptrons (MLP) neural networks to model the demographic characteristics of antenatal clinic attendees in South Africa. The method of cross-validation is used to examine the between-sample variation of neural networks for HIV prediction. MLP neural networks for classifying both the HIV negative and(More)
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