Articles

Background. Mobile Health (mHealth) is a hot research and development topic due to massive spread of smartphones and their high technical performance. Mobile apps for health vary in their functions, from dietary assistance and planning physical activities to “take a drug” reminding and others.
Aim: Assessing the capabilities of existing mobile apps for collecting personal medical data (lab results, radiography scans etc.).
Materials and methods. We performed a systematic search and analysis of...

Introduction. Cardiovascular diseases remain the leading cause of death globally due to the global trend of aging. Mobile medicine — mHealth — is gaining more popularity each year. In this paper, we consider the effectiveness of mHealth in the prevention of cardiovascular events.
Materials and methods. The study was performed in accordance with PRISMA checklist. Original studies published in 2018-2022 were considered for inclusion in systematic review. Еlibrary, PubMed, Scopus, Google Scholar и...

The paper covers international experience in regulating the use of medical data for the development of artificial intelligence systems (AI) using machine learning methods. High-quality medical data sets are required for successful implementation of AI in medical practice and for higher efficiency of clinical and managerial decision-making. Such data sets are impossible to acquire, store and use without appropriate legal and regulatory framework that takes into account the interests of all participants...

The article presents originally developed intelligent decision support tools designed for precancerous lesions and tumors of the oral mucosa diagnostics.
Background. There is well recognized need for better primary health care in patients with suspected maxillofacial tumors.
Aim: develop intelligent decision support tools for tumors of the oral mucosa diagnostics.
Methods. Developed method was based on generalization of the practicing doctors experience. Diagnostic parameters of the disease were...

Background. The development and implementation of medical information systems make it possible to simplify and automate many processes in medical organizations. At the same time, the amount of data on patients’ health is constantly accumulating which allows solving many problems related to the prediction and diagnosis of diseases.
Aim. To study approaches to processing of Russian unstructured medical texts and to predicting certain groups of diseases based on machine learning methods.
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Background. Strategic management of healthcare which, among all, includes modern digital technologies, has increasing importance in the light of non-communicable diseases burden.
Aim. To develop an tool which evaluates and predicts the digital maturity of healthcare, accounting for the strategic importance of combating chronic non-communicable diseases
Materials and methods. We performed an analytical study, making a systematic review of international experience, analysis and adaptation of the...

Aim: to develop and test a methodology for assessing the maturity of healthcare software based on artificial intelligence (AI).
Materials and methods. The methodology for developing a maturity matrix for AI-based healthcare software is based on published data and on an analysis of our own practical experience obtained during the «Experiment on the use of innovative technologies in the field of computer vision for the analysis of medical images and further application in the Moscow healthcare system...

Here we describe building a control impact intended to medically suppress tumor growth. The synthesis of control has been carried out using the method of linearization of a nonlinear system with state feedback. As a result of the study, a control law was obtained that provides the system with local stability, which translates into cessation of tumor growth in physical sense. The adequacy of the tumor growth model is achieved by constructing it using a self-organization algorithm with trend reser...

Causative relationships of microbiota with the human’s health and diseases are one of the most challenging issues in modern microbiology. Progress in this field could provide new tools for diagnosis, prophylaxis, and treatment. A new automated approach is proposed, as an addition to the methods of multidimensional statistical analysis. This approach is based on a planar projection of multidimensional analytical data and is distinguished by technological simplicity and clarity of the process of operational...

New measures to decrease the burden from cardiovascular morbidity are of great socio-economic importance. The aim of the study was to create artificial intelligence technology incorporating various methods and approaches for presenting and using knowledge to assess and predict individual risks of developing cardiovascular events. The following risk presenting models were used: scoring system, multivariate Weibull and logistic regression, artificial neural networks; an ontological approach for ex...

Information technologies in modern continuous professional education (CPE) of medical workers are playing an increasingly active role, becoming the basis for the training organization. Aiming to substantiate the strategy for the further development of CPE, we conducted a questionnaire survey of doctors (n=211) immersed in new forms of training using distance learning technologies. Furthermore, regulatory documents were provided that should become a basis for creating conditions f...

The problem of early and timely accurate diagnosis of rare hereditary diseases is global. The use of physician-assisted computer systems could solve it. There are various foreign medical decision support systems. However, there are currently no domestic functioning systems to resolve these issues.
The aim of this study is to improve the timeliness and accuracy of making a correct diagnosis in patients with signs of hereditary lysosomal storage diseases using an intelligent computer decision support...

It is very important to balance the processes of creating the simplest and most effective predictive models in medicine. The predictors in the model determine its quality and practical relevance but selecting them is not always easy. The aim of the study is to compare different methods of prediction selection to create medical prognostic models.
Methods. We compare simple methods, such as correlation, predictor filtering based on basic statistics, and Hosmer-Lemeshow univariate analysis, with more...

There is a trend in the healthcare of the Russian Federation for the development and implementation of various information systems, including medical information systems of medical organizations (MIS MO), aimed automation of diagnostic, treatment, administrative, auxiliary and other processes, as well as radiological information systems (RIS), designed to automate the service of radiation diagnostics and radiology. Many of the currently utilized MIS were developed 10 and more years ago, are base...

The success and wide-range applications of artificial intelligence (AI) technologies and, in particular, deep learning neural networks methods have led us to a clear understanding of two main problems: the problem of errors (the reliability problem) and the problem of explicitly explaining the decisions made by AI (the explanability problem). These problems are closely related: unexplained AI errors can happen again and again. This is completely unacceptable from the pers...

Auscultation is a classic method of examining patients with respiratory and cardiovascular pathologies. Auscultation is a subjective method, its diagnostic accuracy is highly dependent on the doctor’s experience. Electronic stethoscopes can increase the volume of audio recordings, eliminate noise, and store and transmit sound to a computer or smartphone. Wavelet transform, Butterworth filter, low and high pass filters are used to filter the resulting audio recordings. Machine learning methods, w...

Background. Long-term outcomes of screening programs are challenging to evaluate in randomized clinical trials. The role of predictive modeling is becoming increasingly popular in oncology. Modeling the interventions consequences in oncology is based, among other things, on the use of toolkits, denoted by the term «mathematical oncology» Aim. To study approaches to modeling screening scenarios for breast cancer, aimed at developing tools to support medical decision-making in the healthcare syste...

Currently, there are no unified methodological approaches to diagnose certain diseases, syndromes, symptoms, where distant diagnostics and telemedicine-based treatment prescription are legal and feasible. There are limited and empirically generated lists of pathological conditions, accounting for possible risks. The development of regulatory and legal support for telemedicine-based medical care should be based on a scientific approach, providing for safety and quality assurance. Objective: to de...

Background. Considering the growing interest of researchers and clinical specialists in algorithms for processing medical data, the prospects for the applied application of such approaches have significantly increased, primarily, involving the use of deep neural networks in the tasks of detecting pathological areas. However, the use of such approaches is associated with a low level of localization accuracy, insufficient to translate the developments into the field of assistive systems for making...

The article proposes technique and results for pre-project research and design of automated information systems in relation to business process management systems of medical organizations on the example of monitoring the implementation of regulations at the departments of nephrology and hemodialysis. When developing the system, an original method of system analysis and modeling of business processes was used based on the experience of the divisions of a private network medical company working in...