Direct and inverse problems of clinical practice when analyzing thermometry data

The mathematical basis for the analysis of clinical research results is the fitting of a pre-selected model (for example, a linear combination of basis functions) to experimental data with one of the quality criteria (for example, with the least squares criterion). However, whatever the selected model is and whatever the quality criterion of fitting is, such a direct problem of analysis does not provide a basis for understanding the dynamic laws of biophysics. It happens because of their complexity or obscurity, which is dictated by the temporal behavior of the observed data. This paper studies what the benefits or advantages of the inverse problem of mathematical modeling of such laws are when it is included in the analysis of natural or experimental data.