Iterative Models of Bioimpedance in Intelligent Systems for Early Diagnosis of Infectious Diseases

As a result of the study, fundamentally new results have been obtained, which make it possible to create intelligent decision support systems for the diagnosis of infectious diseases. A bioimpedance analysis model has been created, based on multifrequency bioimpedance measurement, which allows decomposition of biomaterial impedance into structural elements. On the basis of the proposed model, descriptors were formed, intended for classifiers executed on trained neural networks. To obtain descriptors, multifrequency sounding of the biomaterial was carried out, on the basis of which Cole's graphs were constructed. Using iterative algorithms and these graphs, Voight models of the biomaterial impedance were obtained. The parameters of these models are used as descriptors for the trained classifiers.