57 -3 (89) 2026 - Pulatova P.H. - THE ROLE OF ARTIFICIAL INTELLIGENCE IN CARDIOLOGY

THE ROLE OF ARTIFICIAL INTELLIGENCE IN CARDIOLOGY

Pulatova P.H. - Bukhara State Medical Institute named after Abu Ali ibn Sina

Resume

Cardiovascular diseases (CVDs) remain the leading cause of mortality and disability worldwide. In recent years, rapid advancements in artificial intelligence (AI) technologies have profoundly transformed approaches to the diagnosis, risk assessment, and management of cardiac conditions. The application of machine learning and deep neural networks enables the processing and interpretation of extensive and complex medical datasets, including electrocardiographic recordings, medical imaging results, genetic information, and clinical-laboratory parameters. Integration of AI-driven algorithms enhances diagnostic accuracy, facilitates earlier detection of cardiovascular abnormalities, and supports the development of personalized therapeutic strategies. This review provides a comprehensive analysis of current applications of artificial intelligence in cardiology, highlighting key advantages, existing limitations, and future prospects for its implementation in clinical practice.

Keywords: artificial intelligence, cardiovascular diseases, cardiology, machine learning, electrocardiography, cardiovascular risk prediction

First page

353

Last page

357

For citation:Pulatova P.H. - THE ROLE OF ARTIFICIAL INTELLIGENCE IN CARDIOLOGY//New Day in Medicine 3(89)2026 353-357 https://newdayworldmedicine.com/en/new_day_medicine/3-89-2026

List of References

  1. Jain S, Elias P, Poterucha T, Randazzo M, Lopez Jimenez F, Khera R, et al. Artificial Intelligence in Cardiovascular Care – Part 2: Applications. J Am Coll Cardiol. 2024;83(24):2487–2496. doi:10.1016/j.jacc.2024.03.401.
  2. Elias P, Jain S, Poterucha T, Randazzo M, Lopez Jimenez F, Khera R, et al. Artificial Intelligence for Cardiovascular Care – Part 1: Advances. J Am Coll Cardiol. 2024;83(24):2472–2486. doi:10.1016/j.jacc.2024.03.400.
  3. Cai Y, Cai YQ, Tang LY, Wang YH, Gong M, Jing TC, et al. Artificial intelligence in cardiovascular risk prediction models. BMC Med. 2024;22:56. doi:10.1186/s12916-024-03273-7.
  4. Dey D, Slomka P, Leeson P. Artificial Intelligence in Cardiovascular Imaging. Eur Heart J. 2022;
  5. Topol E. Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again. New York: Basic Books; 2022.
  6. Johnson K., Torres Soto J. Artificial Intelligence in Cardiology. Circulation. 2023.
  7. Attia Z. Artificial Intelligence in Cardiovascular Medicine. Nature Reviews Cardiology. 2023.
  8. Esteva A., Robicquet A. A guide to deep learning in healthcare. Nature Medicine. 2019.
  9. Ouyang D., He B. Video-based AI for echocardiography interpretation. Nature. 2020.
  10. Krittanawong C. Machine learning prediction in cardiovascular disease. European Heart Journal. 2020.

    file

    download