Bovine brucellosis is an infectious illness caused mainly by Brucella abortus that may affect domestic and wild animals. Accurate and fast diagnosis is critical for disease control and eradication. Thus, we have identified Brucella abortus antibodies in bovine serum by exploring the agglutination process that is carried out when positive samples are mixed with the antigen. In this case, when placed above the on-chip integrated waveguide, the reaction led to scattering spots that indicated the positive serum. The monitoring was performed through optical images over time and analyzed by artificial neural network. Classification models were able to differentiate the positive from the negative samples with 81.25% accuracy. This work may represent a breakthrough for the diagnosis of other infectious diseases.
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