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Trends in the digitalization of business open up opportunities for the use of fundamental approaches to the development of enterprise architecture in the creation of appropriate methodologies.

The article presents the experience of artificial intelligence application in research process. The article contains general information about basic concepts of machine learning (clustering and visualization), as well as considers more detaily an experience of clinical testing. The effectiveness of applying Data Analysis methods and means as one of the research stages is demonstrated on the example of a case on processing medical information using algorithms of machine learning: solving the problem on diagnostic value of the proposed indicator (FTF) for determining target age groups. Implementation of such approach of digital transformation improves the operational effectiveness of researches, as well as quality and availability of final technological products being developed - software for solving expert problems.

This review describes the history of development of a new line of chemical reagents that prompts to significantly reevaluate the application of scanning electron microscopy (SEM) in medical and biological studies, particularly in ophthalmology; considers the establishing of SEM as an analytical method; covers the problems in its application associated with the needs of clinical medicine and the complexities of biological sample preparation for electron microscopy. The article also presents in chronological order the technical solutions associated with creating a unique line of reagents for supravital staining. The multitude of technical solutions allows considering SEM as a method of express diagnostics. The review discusses examples of practical application of these methods for solving certain cases in clinical ophthalmology. The niche of SEM is considered among other methods of clinical diagnostics, as well as its future development involving the use of artificial intelligence.

The Aim of the Study: Was to compare the prevalence and structure of sudden death from cardiovascular diseases (CVD) in the structure of nonviolent death in Moscow Region as a representative of the large region and St. Petersburg as a city of federal importance. Frequency and structure of this parameter, as well as its dynamics were analyzed. The comparison of obtained results with data of Federal State Statistics Service was done. Nonparametric analysis of the initial data has been conducted. Clustering and visualization, based on the following parameters of initial sample, have been done: «death rate from CVD in the structure of nonviolent death», «morbidity rate», «incomes» and «unemployment rate». Correlation dependences between death rate from CVD according to the Form №42 and mentioned parameters of medical and social state of the subject have been determined. Dependences between sudden death rate from CDV and a number of medical and social parameters have been established.

The objective is to study the prevalence and rate of sudden death from cardiovascular diseases (CVD) in the structure of non-violent death in people under 35 in the Tula region as a representative of a small region of the Russian Federation. A comparison with the data of the Federal State Statistics Service was made. The overall trend was determined. A non-parametric analysis of the initial data, clustering and visualization were performed based on the following parameters of the initial sample: «mortality rate from cardiovascular diseases (CVD) in the structure of non-violent death,» «morbidity,» and «number of doctors in the region.» The correlation of mortality from CVD according to Form 42 and the specified indicators of the medical and social status of the region was determined. The relationship between the rate of CVD-related sudden death and specified medical and social indicators was established.

The purpose of the study is to study the prevalence and frequency of sudden death (SD) from cardiovascular diseases (CVD) in the structure of non-violent death, taking into account the socio-economic development of the constituent entities of the Russian Federation. We analyzed the frequency of this indicator, compared it with the data of the Federal State Statistics Service, and determined the overall dynamics. We conducted a non-parametric analysis of the initial data, carried out clustering and visualization based on the following parameters of the initial sample: «CVD mortality in the structure of non-violent death», «morbidity» and «per capita income level». Correlation dependences of the level of mortality from CVD according to the form 42 on the indicated indicators of the socio-economic condition of the subject were determined. Identified subjects of the Russian Federation with an increase in mortality from CVD; established the dependence of the level of VS on CVD and a number of medical and economic indicators.

The paper presents the results of a comparative epidemiological study of thermal injury and fatal hypothermia based on the results of consolidated reports of the Bureau of Forensic Medicine of the Moscow Department of Health for 2017-2019. It was analyzed the archival material for three calendar years. It was used a continuous retrospective research method with an assessment of the general aggregate of the death incidence from thermal injury and hypothermia in Moscow in 2017-2019 by means of nonparametric statistical methods. Deaths from thermal injury and hypothermia are the most often accidents. The incidence of this type of death is characterized by ups and downs depending on the season. May, January and December are the most dangerous for burns. A similar pattern, with the exception of May, was noted for hypothermia. It was found that men aged 50-70 and women of 70-90 years old die most often. It was determined that most social characteristics (education, being married, etc.) alter the average age when deaths occur. The results obtained provide statistical justification for further more thorough study of thermal injury and hypothermia.

This paper demonstrates the need for an integrated approach to improve the accuracy of corpse age calculation based on measurements of a heterogeneous nature and conditions of partially distorted or incomplete data, using modern information intelligent technologies. A generalized algorithm developed on the basis of various mathematical methods of primary data processing and the extraction of different structures is presented, in addition to the reliability of the information.