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      • Assessing clinical impact of HIV infection in children by knowledge driven data mining

        Kanarkard, W.,Patumwan, P.,Adams, R.,Davey, N. 대한전자공학회 2007 ITC-CSCC :International Technical Conference on Ci Vol.2007 No.7

        This paper proposes the development of a computerised decision aid using knowledge driven data mining that provides the assessment of clinical care during pregnancy and the impact of HIV infection in her children who has a viral transmission from mother. HIV infection and AIDS have severely disrupted child mortality and child health services in many developing countries including Thailand. This study validated the predictive power of data mining algorithms by comparing the performance of two decision tree algorithms, C4.5 and ID3 using the test set of 1,773 pregnant women and the training set of 2,548 pregnant women. Overall performances of these two algorithms were 99.73% of accuracy. In addition, the C4.5 algorithm performed better than the ID3. The decision tree algorithms not only identified but also provided decision rules for identifying critical factors in clinical care that could prevent the HIV transmission from mother to child.

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