A comparison of imputation and prediction methods for classification of Chagas disease
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American trypanosomiasis, also known as Chagas disease, is a parasitic infectious disease that is particularly devastating for indigenous populations in Latin America who often lack access to diagnostic testing. Previously, logistic regression models have been proposed to aid in the prediction of Chagas positivity prior to diagnostic testing in order to more effectively allocate limited resources. This thesis demonstrates the use of random forests to impute missing data and classify Chagas disease positivity in a population of indigenous communities in Sierra Nevada de Santa Marta, Colombia and ...