A new approach based on the serological tests and the Delayed Hyper Sensitivity Tests for the diagnosis of canine leishmaniasis

Abstract

Several responses in the form of serological tests ELISA (Enzyme Linked Immuno Sorbent Assay), IIF (Indirect Immuno Fluoresence) and DHST (Delayed Hyper Sensitivity Tests) can be used to detect leishmania parasite infection in dogs. In this paper, we propose a new method to select the most discriminative tests based on determinant criterion. So, the diagnosis of canine leishmaniasis (CanL) can be improved by reducing the number of features. Moreover, an artificial neural networks (the Multilayer Preceptron neural network) is applied to classify subjects into two groups: positive (sick) and negative (not sick). The correlation between the physical and the pathological state of subjects is specified with multiple attempts. These methods are obtained with considering chain of experiences that allow for fairly reliable and highly effective results which enable us to develop an efficient way to estimate the diagnosis of this disease. After many experiments, we notice that the best combination of the three studied tests is the DHST and IIF tests.