Articles

The study attempted to test experts' assumptions about the difference in the genetic mechanisms of the formation of emotional and volitional deficits in schizophrenia with predominance of negative disorders. The aim of the study is to create empirical theory of these two phenomena using an approach based on JSM-method for automated research support (JSM-method ARS). Polymorphisms of four genes associated with schizophrenia (BDNF, 5HTR2A, HTTLPR, ZNF804A) and clinical data presented as PANSS score...

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 ...

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 ...

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 a...

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 ...

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...

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) ...

Cartographic presentation of information is especially in demand and visual for covering global and regional events, as well as assessing the location of stationary and non-stationary objects in the study area. Geoinformation systems (GIS) in epidemiological surveillance of parasitic diseases provide collection, storage, processing, access to information, display and dissemination of spatially coordinated data that can be used to solve scientific and applied problems: analysis, monitoring, assessment,...

The application of machine learning in healthcare, as one of the more general artificial intelligence technology, has shown enormous potential for improving diagnostic and treatment outcomes for various conditions. However, success of AI-based software largely depends on the availability of high-quality medical datasets and the infrastructure built to streamline its management. Creating relevant, representative and accurately labeled datasets is a complex and expensive task that requires diverse...

The Unified national medical nomenclature (UNMN) has been under development since 2022 with using the Unified Medical Language System (UMLS) Metathesaurus and other sources. UNMN is a terminological system based on ontological approach and potentially applicable in Russian language medical text annotating. Currently, terms from different clinical branches are being added to UNMN utilizing both automatized and expert ways. Often in medicine abbreviations allow expressing the meaning of the concepts...

Implementation of Artificial Intelligence (AI) is considered one of the most promising directions in the digital transformation of healthcare. Such systems can improve the quality of therapeutic and diagnostic processes and the efficiency of planning and managing the healthcare industry. However, the potential of AI to enhance public health indicators and improve the functioning quality of the healthcare system is inextricably linked to ethical issues arising from the specific aspects of their creation...

Aim. To demonstrate the special aspects of dataset creation for neuroimaging using the example of preparing a dataset with computed tomographic images of the brain with and without signs of intracranial hemorrhage.
Methods. The creation of the dataset is based on the methodology developed by the Scientific and Practical Clinical Center for Diagnostics and Telemedicine (regulations for preparing the dataset), which is carried out in 4 stages: planning (selection of the necessary keywords for the...

Aim: To evaluate the experience of using software based on artificial intelligence technologies as part of the Moscow experiment on the use of innovative technologies in the field of computer vision for the analysis of medical images.
Material and methods: A retrospective study was conducted. The work includes the conclusion outputs of 3 AI services on 822 thousand fluorographic studies for the period from 05.01.2022 to 29.12.2022. Pathology was present in 28,341 studies (3.4%). The assessment ...

Aim. To study the possibilities of self-remote monitoring of blood pressure and heart rate in high-risk pregnant women.
Material and methods. Women from 18 to 45 years old with hypertension (chronic and gestational), a history of preeclampsia, a high level of preeclampsia risk (above 1:100), body mass index (BMI) > 30 kg/m2 were included in the study to test self-monitoring of blood pressure using the MedSenger platform. The patients used a home tonometer to measure blood pressure and heart rate...

Background: Due to the National Strategy for the Development of Artificial Intelligence, large-scale digitalization of healthcare is taking place in the Russian Federation, which leads to huge number of various practical and scientific tasks emergence of, which in turn require convenient tools to solve them. ROC analysis tool is one of them, which was developed and successfully applied within the framework of the project «Experiment on the use of innovative technologies in the field of computer ...

Aim: to develop a model predicting the incidence of newly diagnosed HIV infection in the subjects of the Russian Federation using machine learning methods.
Materials and methods: The initial data were obtained from the Federal statistical observation Form No. 61 and Rosstat data on the average annual population of 85 subjects of the Russian Federation (2016-2022). We made a comparison of machine learning methods and their ensembles in the construction of a regression model for predicting the incidence...

Background. Early axial spondyloarthritis (axSpA) diagnostics is a difficult task requiring clinical decision support (CDS) making. Currently, there is a big unstructured data applicable in CDS systems development. Semantic data analysis is a complex issue to solve, and unified tools for named entity recognition are required. The biggest data source for biomedical text annotation is the Unified Medical Language System (UMLS) Metathesaurus. It includes more than 11 million atomic terms for writing...

Aim: Comparative assessment of the quality of predictive models of in-hospital mortality (IHM) in patients with ST-segment elevation myocardial infarction (STEMI) after percutaneous coronary artery intervention (PCI), developed on the basis of predictors in continuous, dichotomous and multilevel categorical forms.
Materials and methods: This was a single-center retrospective study analyzing data from 4677 medical records of patients with STEMI PCI who were treated at the Regional Vascular Center...

The article covers methods and procedures for developing a neural network decision support system when choosing the tactics of surgical intervention on coronary heart vessels. The system is designed to advise a wide range of practicing cardiologists and cardiac surgeons when deciding on the tactics of surgical intervention in patients with conditions associated with compromised coronary vessels. Based on a mathematical model taking into account a number of factors and the outcomes of previously ...

This article discusses the experience of using data visualization tools in the preparation of territorial planning schemes for regional health systems. The article also covers trends in the development of visualization tools and the competencies necessary for decision makers to use these tools effectively in making managerial decisions.