A Jones matrix model of biological fluids dehydrated films (facies) optical anisotropy is proposed. The relationships between the blood facies phase (birefringence) anisotropy parameters and the Jones matrix elements real and imaginary components are determined. The experimental testing results of the blood facies polarization matrix thesiography polycrystalline architectonics method with linear and circular birefringence coordinate distributions reproduction are presented. Integral blood facies phase anisotropy maps are presented. Scenarios changes of 1st - 4th orders central statistical moments, which characterize blood facies phase anisotropy maps are determined and physically analysed. The results of the Jones matrix thesiography method clinical testing is presented. Very good and balanced accuracy level has been achieved in the temporal differentiation of the long-term outcomes of patients who have undergone COVID-19. The prospects for further research using an integrated approach based on polarization analysis of laser-induced auto fluorescent images of supramolecular networks of blood facies are indicated.
For many years, the medical community has used experimental and clinical observation methods to study the course of various diseases. This approach has a high degree of validity, but it also has some limitations, such as high costs and difficulty in controlling all influencing factors and individual variability. In this regard, there is a need to create new methods for studying and predicting the course of diseases. One of these tools is a mathematical model. This study considers the possibility of mathematical modeling of the effectiveness of anti-tuberculosis treatment, based on the levels of biochemical markers of tuberculosis, namely Human-beta-defensin-1 (HBD-1), ferritin and interleukin-6 (IL-6). Based on a study of the relationships between the effectiveness of anti-tuberculosis treatment and the levels of Humanbeta-defensin-1, ferritin and interleukin-6, a mathematical model was created that allows predicting the effectiveness of anti-tuberculosis treatment based on determining biochemical markers at the beginning of treatment and after 60 days of anti-tuberculosis therapy with sensitivity and specificity of at least 88%.
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