Sectional session “Cardiovascular continuum: from ACS to CHF” as part of the anniversary conference on cardiology in Surgut
On September 28-29, the International Laboratory of Bioinformatics of the National Research University Higher School of Economics together with the Scientific and Educational Center of the Medical Institute of the Khanty-Mansiysk Autonomous Okrug - Ugra "Surgut State University" for the purpose of implementing the project "Mirror Laboratories" held a sectional session "Cardiovascular continuum: from ACS to CHF"
At Surgut State University, on September 28-29, the Interregional Scientific and Practical Conference of the Ural Federal District “Cardiology 2023: Practice, Science and Innovation” opened, dedicated to the 25th anniversary of the region’s cardiac surgery service. The organizers of the event are the Ugra Department of Health, the District Cardiology Clinic, the Department of Cardiology of the Medical Institute of Surgut State University.
The program of the Interregional Scientific and Practical Conference includes: 15 sectional sessions, a round table, master classes, an exhibition of medical equipment, two discussion platforms and a symposium. All events are in one way or another related to issues of emergency cardiology, treatment of patients with chronic heart failure, opportunities and prospects for cardiovascular surgery, and new challenges of endovascular surgery.
The International Laboratory of Bioinformatics of the National Research University Higher School of Economics together with the Scientific and Educational Center of the Medical Institute of the Budgetary Institution of Higher Education of the Khanty-Mansiysk Autonomous Okrug - Ugra "Surgut State University" for the purpose of implementing the project "Mirror Laboratories" "Machine Learning Technologies in Predicting the Outcomes of Acute Coronary Syndrome" held a sectional session "Cardiovascular continuum: from ACS to CHF" as part of the anniversary conference.
The breakout session was dedicated to the joint scientific and practical research “Machine learning technologies in predicting the outcomes of acute coronary syndrome”, the main result of which is the creation of a prognostic system based on artificial intelligence algorithms for assessing the risks of an adverse event for the personalized management of patients with myocardial infarction after discharge from the hospital.