<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Significant progress in the field of Artificial Intelligence (AI) has been highlighted over the past decade. Its continuously evolving applications have found various uses in the medical field, focusing on prevention, screening, and treatment for a wide range of conditions, as well as anticipating their progression. In the field of cardiology, various AI models have proven their effectiveness in interpreting data from technologies such as electrocardiography and imaging, demonstrating their utility in interpreting echocardiography, nuclear magnetic resonance, as well as computer tomography. The integration of artificial intelligence into electrocardiogram (ECG) analysis not only improves the accuracy of diagnosis but also facilitates the recommendation of personalized and optimal treatment for each patient. Cardiovascular imaging has become an extremely advanced research field within AI, with echocardiography being an excellent method for non-invasive evaluation, both quantitatively and qualitatively, of cardiac function. The implementation of artificial intelligence in analyzing images obtained through nuclear magnetic resonance and computer tomography has also been successful in identifying specific conditions, such as myocardial ischemia or obstructive coronary artery disease.</p>
</abstract>

Significant progress in the field of Artificial Intelligence (AI) has been highlighted over the past decade. Its continuously evolving applications have found various uses in the medical field, focusing on prevention, screening, and treatment for a wide range of conditions, as well as anticipating their progression. In the field of cardiology, various AI models have proven their effectiveness in interpreting data from technologies such as electrocardiography and imaging, demonstrating their utility in interpreting echocardiography, nuclear magnetic resonance, as well as computer tomography. The integration of artificial intelligence into electrocardiogram (ECG) analysis not only improves the accuracy of diagnosis but also facilitates the recommendation of personalized and optimal treatment for each patient. Cardiovascular imaging has become an extremely advanced research field within AI, with echocardiography being an excellent method for non-invasive evaluation, both quantitatively and qualitatively, of cardiac function. The implementation of artificial intelligence in analyzing images obtained through nuclear magnetic resonance and computer tomography has also been successful in identifying specific conditions, such as myocardial ischemia or obstructive coronary artery disease.

Artificial Intelligence in Cardiology

Department of Internal Medicine I, Faculty of Medicine

University of Medicine and Pharmacy “Grigore T. Popa”

Department of Cardiovascular Rehabilitation

Internal Medicine

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Artificial Intelligence in Cardiology"}

Significant progress in the field of Artificial Intelligence (AI) has been highlighted over the past decade. Its continuously evolving applications have found...

Artificial Intelligence in Cardiology

Publicado en línea: 12 jun 2024

Páginas: 55 - 64

DOI: https://doi.org/10.2478/inmed-2024-0288

Palabras clave
artificial intelligence, echocardiography, valvopathies, coronary artery disease

© 2024 Maria Magdalena Leon et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Artificial Intelligence in Cardiology

Publicado en línea: 12 jun 2024

Páginas: 55 - 64

DOI: https://doi.org/10.2478/inmed-2024-0288

Palabras claveartificial intelligence, echocardiography, valvopathies, coronary artery disease

© 2024 Maria Magdalena Leon et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Palabras clave
artificial intelligence, echocardiography, valvopathies, coronary artery disease