MD&IT №4 2022

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...