Modern capabilities of artificial intelligence technologies in cardiovascular imaging

• Published in: Digital diagnostics Vol. 6; no. 1; pp. 116 - 129
• Main Authors: Islamgulov, Almaz Kh, Bogdanova, Alina S., Sufiiarov, Damir I., Chernyavskaya, Alina V., Bairakaeva, Elena R., Maksimova, Anastasia A., Nemychnikov, Nikita V., Bikieva, Diana R., Shakhmaeva, Alsu I., Burdina, Lyubov A., Bolekhan, Aleksandr V., Akimov, Egor I., Shurakova, Zilya Z.
• Format: Journal Article
• Language: English
• Published: 25.03.2025
• ISSN: 2712-8490; 2712-8962
• DOI: 10.17816/DD640895

Cardiovascular diseases are the leading cause of disability and mortality worldwide. The emergence of new technologies and integration of artificial intelligence with machine learning have broadened opportunities for doctors to improve the effectiveness of diagnostic and therapeutic measures. The development of artificial intelligence technologies, particularly in the fields of machine and deep learning, is rapidly attracting the interest of clinicians in creating novel, integrated, reliable, and efficient diagnostic methods to provide medical care. Cardiologists use various imaging-based diagnostic techniques, which provide more extensive quantitative data about patients. This review summarizes current literature on the application of artificial intelligence technologies in diagnosing cardiovascular diseases and identifies knowledge gaps that require further research. Machine and deep learning methods are widely used and have shown promising results in cardiology. Convolutional neural networks have been used to measure cardiac function parameters from echocardiography results. Deep learning algorithms provide more accurate identification of stenosis and calcification in coronary arteries and characterization of plaques in cardiac CT scans. Convolutional neural networks have been employed for tasks such as automatic segmentation of heart chambers and structures, tissue property determination, and perfusion analysis using magnetic resonance imaging results. As artificial intelligence technologies, particularly machine learning, continue to develop, their integration opens up new possibilities. Thus, artificial intelligence technologies are of great interest in healthcare, as they enable the rapid analysis of large amounts of data, demonstrating high effectiveness. artificial intelligence can provide additional assistance to specialists, contributing to enhanced workflow efficiency and improved medical care.