Background. The article presents the results of a review study on the origins of systematic healthcare informatization and the formation of digital healthcare in Russia, as it is now commonly called, since the 60s of the last century, and an analysis of how introduction of digital healthcare methods and technologies, and compulsory medical insurance (CMI) progressed over the years. A comprehensive analysis of the formation and development of digital healthcare on a nationwide scale has not been carried out before, and the corresponding periodization of stages has not been developed. Some facts of digitalization of federal significance, specifically in the history of the development of the CMI system in Russia, were either not published at all, or were published in isolation from the digitalization of healthcare in general and were not analyzed in the general context.
Aim. A systematic review of the main developments in the progress of digital healthcare in Russia and the development of a reasonable periodization of this process, as well as a forecast of promising areas of development, the main of which is patient orientation.
Methods. We performed a search for publications in bibliographic database eLibrary over the years, the search engine for the full text of scientific publications, Google Scholar, the analysis of normative legal acts in force in the territory of the Russian Federation, information analysis of open Internet sources with the use of the Yandex search engine. The search was performed using the following keywords: E-health; digital healthcare; digital transformation; digitalization; stages of development; EGISZ; unified digital circuit. Results. As a result of the study, more than 40 of the most important events of the formation and development of digital healthcare in Russia have been identified, the periodization of the process of digitalization of healthcare has been proposed and justified, starting with the creation of systemic prerequisites at the end of 1993 and from the start of digitalization on the scale of Russia in 2006 to the third stage, ending in 2024. The main trends and forecasts in the field of development of digital healthcare methods and technologies at the promising, fourth stage of digitalization of healthcare from 2025 have been formulated.
Conclusion. Digital healthcare in Russia for a unified system of public health protection started only after the creation of the necessary objective conditions – the mass distribution of IT tools, the introduction of a CHI system and the beginning of the digital transformation of the public administration system in Russia. The article proposes and substantiates the periodization of the process of formation and development of digital healthcare in the Russian Federation, including promising areas and key trends until 2030.

There is increasing interest in using big data of real clinical practice to develop artificial intelligence systems for diagnostic and predictive models of diseases and conditions. At the same time, the quality of this data is usually low due to errors during input, suboptimal architecture of information systems, lack of standardization, etc. The review examines criteria for the reliability of real-world data, the most common problems, and ways to eliminate them: assessing the compliance of the data set with the design of the model being developed, identifying, and removing duplicate records in data sets, handling missing values, detecting, and handling outliers, identifying and handling inconsistencies in data. We conclude that further development of methods for creating data sets based on real-world data is required in terms of improving their quality, can lead to lower quality of the created machine learning models for diagnosis and prognosis

The World Health Organization records an unprecedented increase in global health care spending with a trend of further growth until 2050. Artificial intelligence (AI) technologies are considered one of the key tools for increasing the efficiency of these expenses. One of the information sources that gives an idea of the scale and intensity of extensive research, the solutions found, their concepts and global technology leaders is the world portfolio of patent documents. In this study, a patent analysis of the technological field “Artificial Intelligence in Healthcare” was performed. The results of this analysis proved the research direction to be one of the most dynamically developing scientific and technological trends of the last decade. It has been shown that two key thematic clusters of this direction are the use of machine learning algorithms to create predictive and diagnostic models, and developments in the field of large language models (LLM). Russia is among the top 15 countries in the world in terms of patent activity in the direction of “Technology of language models in medicine,” but remains somewhat behind the leading countries in the number of patent families

Currently, mathematical analysis and three-dimensional modeling represent a new promising way to obtain additional information, which allows the researcher to virtually observe and model complex biomechanical phenomena. Issues of dynamic neck anatomy, as well as the biomechanical characteristics of its individual structures, are of significant practical and theoretical interest regarding many areas of medicine.
Aim: to develop a virtual dynamic model of the human neck and in order to reproduce dynamic processes using the finite element method.
Materials and methods: Biomechanics of physiological processes of the cervical spine were studied using MRI. Finite element mesh generation and contact interactions were performed using HyperMesh software. Material modeling and finite element analysis were performed using Abaqus CAE 6.14 software.
A retrospective analysis of the results of 124 high-quality MRI studies (40 men and 84 women) was conducted. The database included studies that met the inclusion and exclusion criteria. Statistical processing was carried out using MS Excel 2019 in the “Data Analysis” add-on. Parametric indicators were checked for normal distribution in the “descriptive statistics” function, followed by calculation of the significance of the differences in indicators with a “two-tailed Student’s test”. To assess nonparametric indicators, χ2 -Pearson was used to construct contingency tables. To study the dependence of the tg α value on the age of patients in the presence or absence of IVD protrusions, analysis of variance was used for differences in more than two groups using the one-way ANOVA method.
Results: A technique for creating a virtual dynamic neck model has been developed. The results of finite element analysis of the C3-C5 segment under axial loading were compared with in vitro data.
Conclusion: The simulation results gained using the proposed technique are in good agreement with experimental data. The generated biomechanical models make it possible to describe dynamic phenomena in the cervical spine and obtain a wide range of quantitative properties of objects.

The purpose of this study was to evaluate the radiologists’ engagement and satisfaction with artificial intelligence software as a means to support medical decision-making.
A survey of radiologists working in public healthcare facilities under the Moscow Healthcare Department was conducted in 2021 and 2022.
The survey was completed by 333 radiologists in 2021, and by 342 – in 2022. The respondents were CT, MRI, X-ray and MMG specialists of various age and clinical experience. The study found that the physicians’ engagement rate with artificial intelligence more than doubled in 2022 vs. 2021. An assessment of satisfaction with the artificial intelligence technologies in routine clinical practice showed that in 2022 vs. 2021, the opinions shifted from the extreme “excellent” and “unsatisfactory” rates towards moderate “good” and “satisfactory”.
The findings show that artificial intelligence technologies require further improvement from both clinical and technical standpoint, public perception and also as an educational tool for physicians who use artificial intelligence in their routine clinical practice

Background. Telemedicine is an important tool for ensuring the availability of medical care, contributing to the reduction of morbidity and mortality, primarily from chronic diseases. It is necessary to introduce organizational models into clinical practice for the development of telemedicine in our country.
Aim. To form new approaches for monitoring patients using telemedicine technologies in a federal institution. Material and methods. The work on conducting telemedicine consultations (TMC) «doctor-patient» and «doctordoctor » was initiated and promoted in the center of telemedicine of SamSMU. Postoperative telepatronage of patients discharged from the hospital after surgical interventions has been introduced. The fast-track approach has been implemented in surgery and interventional cardiology. Remote monitoring of cardiological patients has been organized. Work has been established on remote monitoring of patients on the waiting list for organ transplantation and after its completion.
Results. The number of TMC conducted in 2022 exceeded the corresponding numbers of 2020 and 2021 by 32.9 and 25.4 times, respectively. The analysis of «doctor-patient» TMC showed an increase in 2022 compared to 2021 by 358 times. The growth in the number of «doctor-doctor» TMC in 2022 compared to 2021 by 2.5 times was noted. 6602 TMC were performed during the implementation of outpatient telepatronage. 284 TMC performed in 2022 allowed monitoring of patients after surgical interventions. The «fast-track» approach made it possible to reduce in-hospital length of stay and provided telemedicine monitoring of 987 patients after cardiac surgery. The practice of remote monitoring allowed for dynamic monitoring of 53 patients on the waiting list for organ transplantation and after transplantation.
Conclusions. The organization of specialized telemedicine centers in medical and preventive institutions contributes to the development of telemedicine technologies in our country and the introduction of the best innovative practices in domestic medicine aimed at improving the quality and accessibility of medical care