Publications

Integration of AI-based software as a medical device into Russian healthcare system: results of 2023

Development, evaluation and validation of machine learning models to predict hospitalizations of patients with coronary artery disease within the next 12 months

Perspectives on the application of large language models in healthcare

Development and testing of new methodical approaches for predicting cardiovascular events in healthy people using machine learning technology based on the «INTEREPID» international research

Obesity grade I: a study of real clinical practice in the Russian Federation

Standardization of implementation of artificial intelligence medical software in terms of digital maturity level

Ethical principles of the development of artificial intelligence systems for healthcare

Development and validation of models to predict total and early-onset preeclampsia in the first trimester of pregnancy using machine learning algorithms

Results of the pilot implementation of artificial intelligence technologies in the healthcare system of the Yamalo-Nenets autonomous okrug

Experience in the application of artificial intelligence technologies for the development of preventive health care on the example of the Kirov region. ManagerZdravoohranenia

Short-term forecasting of mortality rates based on operational data using machine learning methods

Prediction of cardiovascular events using proportional risk models and machine learning models: a systematic review

Retrospective analysis of the prevalence of ischemic stroke and the appointment of anticoagulant therapy in patients with atrial fibrillation depending on the body mass index

State registration of software as a medical device according to the rules of the Eurasian Economic Union (EAEU)

Survey of awareness and opinions of Russian healthcare managers on artificial intelligence

Prevention of febrile neutropenia in oncological patients: real-world data

Atrial fibrillation and chronic kidney disease: main clinical characteristics of patients in selected subjects of the Russian Federation

Ethical problems in the development of artificial intelligence technologies in healthcare

Analysis of Publication Activity and Research Trends in the Field of AI Medical Applications: Network Approach

Artificial Intelligence on Guard of Reproductive Health

Сriteria for the applicability of computer vision for preventive studies on the example of chest x-ray and fluorography

Аn analysis of global experience in regulations on the use of medical data for artificial intelligence systems development based on machine learning

mHealth apps as a tool for the prevention of cardiovascular diseases.

Extraction of medical data from electronic medical records using NLP algorithms

Health Information System Maturity Assessment Methodology

Informatization of healthcare in the Russian Federation: history and results of development

Evolution of research and development in the field of artificial intelligence technologies for healthcare in the Russian Federation: results of 2021

Methodical approach and recommendations for scientific description of creation and validation of machine learning model

Implementing an Artificial Intelligence System in the Work of General Practitioner in the Yamalo-Nenets Autonomous Okrug: Pilot Cross-sectional Screening Observational Study

Electronic medical records as a source of real-world clinical data

Predicting the subclinical carotid atherosclerosis in overweight and obese patients using a machine learning model

Verification of subclinical carotid atherosclerosis as part of risk stratification in overweight and obesity: the role of machine learning in the development of a diagnostic algorithm

Sample Size Calculation for Clinical Trials of Medical Decision Support Systems with Binary Outcome. Sovremennye tehnologii v medicine

Artificial intelligence in the Healthcare of Russia. Laboratory Role

Development of a machine learning model to interpret the results of laboratory diagnostics in order to identify suspected diseases

Artificial intelligence on the doorstep of the laboratory

Principles for building confidence in artificial intelligence systems for healthcare

Feasibility of using artificial intelligence in radiology (first year of Moscow experiment on computer vision)

Prospects for the use of big data in Russian healthcare

THE USE OF THE CLINICAL DECISION SUPPORT SYSTEM to control the accurateness of cardiovascular risk assessment for adult checkup

Global trends in the digital transformation of the healthcare industry

Improvement of cardiovascular risk assessment using machine learning methods

Predictors of endometriosis in infertility

Machine learning based on laboratory data for disease prediction

The role of artificial intelligence in predicting preterm birth

Healthcare in the smartphone: the situation in Russia

COVID-19 pandemic prediction model based on machine learning in selected regions of the Russian Federation

Predicting preeclampsia using artificial intelligence technologies

Hybrid Predictive Modelling for Finding Optimal Multipurpose Multicomponent Therapy

Prevalence of chronic kidney disease according to the CKD Epidemiology retrospective cohort study (Kirov city)

Ethics and digital: from problems to solutions

Retrospective analysis of electronic health records of patients with heart failure: the first Russian experience

Artificial intelligence on guard of reproductive health

Correctness of cardiovascular risk assessment in daily clinical practice

Legal regulation of artificial intelligence software in healthcare in the Russian Federation

Artificial intelligence: predictive analytics of perinatal risks

Predictive analytics technologies in the management of the COVID-19 pandemic

Algorithm for forming a suspicion of a new coronavirus infection based on the analysis of symptoms for use in medical decision support systems

CARDIOVASCULAR DISEASES PREDICTION BY INTEGRATED RISK FACTORS ASSESSMENT BY MEANS OF MACHINE LEARNING

Adapting neural network models to predict 10-year CVD development based on regional data calibration

Feature Extraction Method from Electronic Health Records in Russia

Deep and machine learning models to improve risk prediction of cardiovascular disease using data extraction from electronic health records

Prospects for the use of machine learning methods for predicting cardiovascular disease

Artificial intelligence for cardiovascular risks assessment

The basic recommendations for the creation and development of information systems in health care based on artificial intelligence

Artificial Intelligence in Medicine and Healthcare

Prospects for neural networks and deep machine Learning in creating health solutions

Clinical Decisions Support in medical information systems of a medical organization