Articles filtered by author Gusev A.V..
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MD&IT № 3 2024
Review of methodological approaches to assessing the quality of electronic health records management
Transition to electronic medical records (EMR) is one of the basic directions of digital transformation of healthcare. One of the urgent modern problems of EMR management is the quality of data that are accumulated in modern medical information systems. Given the growing role of EMRs as a source of information for medical decision support systems, the introduction of management elements based on primary data, and the development of research in the field of real-world clinical practice data (RWD),...
MD&IT №1 2024
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 ...
MD&IT №4 2022
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...
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...
MD&IT №4 2022
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...