Articles

Introduction. The introduction of artificial intelligence (AI) technologies in Russian healthcare is an important step to improve the efficiency and quality of medical care. The development of AI technologies helps automate data processing, support physician decision-making and improve predictive analytics.
Aim. Analysis of the results of creation and implementation of software solutions using AI technologies in Russian healthcare.
Materials and Methods: A systematic search for data in the State...

State programs in the field of healthcare informatization implemented in 2011–2021 resulted in over 91% of state and municipal medical organizations implementing various medical information systems. This made it possible to start the transition to electronic medical records (EMR). The extraction of real-world data (RWD) from the accumulated EMRs and subsequent analysis of these data opens new and promising opportunities for the development of domestic healthcare.
Aim: to analyze the RWD extracted...

Objective. The study is devoted to modern forms of case method implementation as a key tool in the development of clinical thinking of doctors. The main factors complicating the creation of situational tasks and limiting the large-scale application of this method in medical education are identified.
Materials and methods. The concept of using large language models (LLM) to reduce the complexity and labor intensity of developing situational tasks in medical education is proposed.
Results. A prototype...

Background. Diagnosis of early-stage chronic kidney disease (CKD) is a global challenge, as late-stage disease is more commonly diagnosed. The development of modeling methods for making management decisions aimed at improving the efficiency of early diagnosis of CKD is an important scientific and practical task, which can be greatly supported by the use of machine learning algorithms (MLA).
Aim. To improve the accuracy of diagnosis of CKD using data from history, clinical-instrumental, genetic ...

This paper considers the problem of simultaneous prescription of a large number of drugs to a patient and consideration of possible risks of polypharmocotherapy. At high risk of polypharmocotherapy it is necessary to revise the prescribed drugs, consider analogs, change the method of administration or reduce the dosage, which requires high qualification and knowledge of the doctor. With automatic risk prediction, it is possible to automate the process of searching for a rational combination of d...

Aim: to study digital health technologies presented in dissertation research in the specialty “Public Health and Healthcare” for 2018-2022.
Materials and methods: We found 194 dissertations posted on the official website of the Higher Attestation Commission in the specialty “Public Health and Healthcare” (02/14/03) for 2018-2022. We identified 72 dissertations which studied the use of digital technologies in healthcare.
The analysis of the obtained data was carried out using the interactive computing...

Цифровые технологии с каждым годом играют все большую роль в медицине. Однако цифровые навыки медицинских работников остаются основным ограничивающим фактором для внедрения все более продвинутых технологических решений. В данном исследовании представлены данные опроса, проведенного на портале Непрерывного медицинского и фармацевтического образования, в котором приняли участие более 18 тысяч медицинских работников. Были выделены и проанализированы группы согласно уровню цифровых компетенций. Был...

Background. Primary hyperparathyroidism (PHPT) is an endocrine disease characterized by excessive production of parathyroid hormone (PTH) and elevated or high-normal blood calcium levels caused by primary pathology of the parathyroid glands. The "classic" complication of PHPT is a decrease in the kidneys filtration function. Parathyroidectomy (PTE) reduces the risks of further deterioration in filtration function; however, in some cases, this is not achieved.
Aim. To develop a mathematical model...

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...

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...

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...

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...