An advanced intelligent ELISA test for bovine tuberculosis diagnosis

Abstract

The control of bovine tuberculosis (bTB) relies first on an optimal diagnosis of the disease. Several tests have been implemented for bTB detection which are generally complex, slow of use and relatively expensive especially in poor countries. A simple rapid, cost effective and efficient automated method for bTB assessment is still needed. Here, we propose a combination of the simple Enzyme Linked Immuno Sorbent Assay (ELISA) test with either the artificial neural network (ANN) analyzing method to effectively diagnose TB in cattle. The proposed method has been experimented on 30 bTB+ and 43 bTB- subjects in the north part of Tunisia, as assessed by the intra dermal reaction test (IDR). The obtained results have reached a 94% of accuracy when applying the ANN. Moreover, the proposed methodology enabled us to reduce the number of the used pathogens-derived antigens to three instead of the standard five antigens-based ELISA. Compared to previous works, the proposed expert system seems to be promising and may prove helpful for the veterinary diagnosis of tuberculosis.