Classification and Prediction Of A Health Status Of HIV/AIDS Patients: Artificial Neural Network Model

Artificial neural network (ANN) is known to identify relationships even when some of the input data are very complex, ill-defined and ill-structured. One of the advantages in ANN is that it can discriminate the linearly inseparable data. This study presents an application of ANN to classify and predict the symptomatic status of HIV/AIDS patients. Even though ANN techniques have been applied to a variety of areas, this study has a substantial contribution to the HIV/AIDS care and prevention planning area. ANN model in classifying both the HIV and AIDS status of HIV/AIDS patients is developed and analyzed. The diagnostic accuracy of the ANN in classifying both the HIV status and AIDS status of HIV/AIDS status is evaluated. Several different ANN topologies are applied to AIDS Cost and Services Utilization Survey (ACSUS) datasets in order to demonstrate the model\`s capability. If ANN design models are different, it would be interesting to see what influence would have on classification of HIV/AIDS-related persons.