The purpose of this work is the authors’ attempt to identify the main phases of information transformation in measurement channels on the example of an optical measurement channel with microprocessor control. The authors include such phases: hardware implementation and analytical representation of an optical sensor’s converting functions and a current-to-voltage converter; based on the methods of experimental computer science, the converting functions and sensitivity are deduced, analytical dependences for estimation of a range of measurement are obtained. It is shown that the choice of information transmission type in the microprocessor measuring channel significantly affects the speed of the measuring channel. Based on the uncertainty in the form of entropy before and after measurements, the amount of information for measuring channels with optoelectronic sensors is estimated. The application of the results obtained in the work allows even at the design stage of physical and mathematical modeling to assess the basic static metrological characteristics of measuring channels, aimed at reducing the stage of development and debugging of hardware and software and standardization of their metrological characteristics.

Individual anatomical features of the paranasal sinuses and dentoalveolar system, the complexity of physiological and pathophysiological processes in this area, and the absence of actual standards of the norm and typical pathologies lead to the fact that differential diagnosis and assessment of the severity of the course of odontogenic sinusitis significantly depend on the measurement methods of significant indicators and have significant variability. Therefore, an urgent task is to expand the diagnostic capabilities of existing research methods, study the significance of the measured indicators, and substantiate the expediency of their use in the diagnosis of specific pathologies in an automated mode. Methods of digital filtering, image segmentation and analysis, fluid dynamics, and statistical and discriminant analysis were used. Preliminary differential diagnosis of odontogenic sinusitis can be performed by densitemetric analysis of tomographic images of the maxillary sinuses, performed using frontal multiplanar reconstructions according to a given algorithm. The very manifestation of the characteristic changes in the densitography of the maxillary sinus allows for the initiation of certain pathological processes and permits the development of the effectiveness of the diagnosis of the pathology of the sinus sinuses, which can be realized automatically in real life.

This study analyzes the existing methods for studying nasal breathing. The aspects of verifying the results of rhinomanometric diagnostics according to the data of spiral computed tomography are considered, and the methodological features of dynamic posterior active rhinomanometry and the main indicators of respiration are also analyzed. The possibilities of testing respiratory olfactory disorders are considered, the analysis of errors in rhinomanometric measurements is carried out. In the conclusions, practical recommendations are given that have been developed for the design and operation of tools for functional diagnostics of nasal breathing disorders. It is advisable, according to the data of dynamic rhinomanometry, to assess the functioning of the nasal valve by the shape of the air flow rate signals during forced breathing and the structures of the soft palate by the residual nasopharyngeal pressure drop. It is imperative to take into account not only the maximum coefficient of aerodynamic nose drag, but also the values of the pressure drop and air flow rate in the area of transition to the turbulent quadratic flow regime. From the point of view of the physiology of the nasal response, it is necessary to look at the dynamic change to the current mode, given the hour of the forced response, so that it will ensure the maximum possible acidity in the legend. When planning functional rhinosurgical operations, it is necessary to apply the calculation method using computed tomography, which makes it possible to predict the functional result of surgery.

The article analytically summarizes the idea of applying Shannon’s principle of entropy maximization to sets that represent the results of observations of the “input” and “output” entities of the stochastic model for evaluating variable small data. To formalize this idea, a sequential transition from the likelihood function to the likelihood functional and the Shannon entropy functional is analytically described. Shannon’s entropy characterizes the uncertainty caused not only by the probabilistic nature of the parameters of the stochastic data evaluation model but also by interferences that distort the results of the measurements of the values of these parameters. Accordingly, based on the Shannon entropy, it is possible to determine the best estimates of the values of these parameters for maximally uncertain (per entropy unit) distortions that cause measurement variability. This postulate is organically transferred to the statement that the estimates of the density of the probability distribution of the parameters of the stochastic model of small data obtained as a result of Shannon entropy maximization will also take into account the fact of the variability of the process of their measurements. In the article, this principle is developed into the information technology of the parametric and non-parametric evaluation on the basis of Shannon entropy of small data measured under the influence of interferences. The article analytically formalizes three key elements: -instances of the class of parameterized stochastic models for evaluating variable small data; -methods of estimating the probability density function of their parameters, represented by normalized or interval probabilities; -approaches to generating an ensemble of random vectors of initial parameters.

Background: Today, cardiovascular diseases cause 47% of all deaths among the European population, which is 4 million cases every year. In Ukraine, CAD accounts for 65% of the mortality rate from circulatory system diseases of the able-bodied population and is the main cause of disability. The aim of this study is to develop a medical expert system based on fuzzy sets for assessing the degree of coronary artery lesions in patients with coronary artery disease. Methods: The method of using fuzzy sets for the implementation of an information expert system for solving the problems of medical diagnostics, in particular, when assessing the degree of anatomical lesion of the coronary arteries in patients with various forms of coronary artery disease, has been developed. Results: The paper analyses the main areas of application of mathematical methods in medical diagnostics, and formulates the principles of diagnostics, based on fuzzy logic. The developed models and algorithms of medical diagnostics are based on the ideas and principles of artificial intelligence and knowledge engineering, the theory of experiment planning, the theory of fuzzy sets and linguistic variables. The expert system is tested on real data. Through research and comparison of the results of experts and the created medical expert system, the reliability of supporting the correct decision making of the medical expert system based on fuzzy sets for assessing the degree of anatomical lesion of the coronary arteries in patients with various forms of coronary artery disease with the assessment of experts was 95%, which shows the high efficiency of decision making. Conclusions: The practical value of the work lies in the possibility of using the automated expert system for the solution of the problems of medical diagnosis based on fuzzy logic for assessing the degree of anatomical lesion of the coronary arteries in patients with various forms of coronary artery disease. The proposed concept must be further validated for inter-rater consistency and reliability. Thus, it is promising to create expert medical systems based on fuzzy sets for assessing the degree of disease pathology.

Our work uses a polarization matrix formalism to analyze and algorithmically represent optical anisotropy by open dehydration of blood plasma films. Analytical relations for Jones matrix reconstruction of optical birefringence maps of protein crystal networks of dehydrated biofluid films are found. A technique for 3D step-by-step measurement of the distributions of the elements of the Jones matrix or Jones matrix images (JMI) of the optically birefringent structure of blood plasma films (BPF) has been created. Correlation between JMI maps and corresponding birefringence images of dehydrated BPF and saliva films (SF) obtained from donors and prostate cancer patients was determined. Within the framework of statistical analysis of layer-by-layer optical birefringence maps, the parameters most sensitive to pathological changes in the structure of dehydrated films were found to be the central statistical moments of the 1st to 4th orders. We physically substantiated and experimentally determined the sensitivity of the method of 3D polarization scanning technique of BPF and SF preparations in the diagnosis of endometriosis of uterine tissue.