| Autor: |
Patrascanu OS; Department of Cardiology, University Emergency Hospital of Bucharest, 169 Splaiul Independentei St, 050098 Bucharest, Romania., Tutunaru D; Faculty of Medicine and Pharmacy, Dunarea de Jos University of Galati, 35 AL Cuza St, 800010 Galati, Romania., Musat CL; Faculty of Medicine and Pharmacy, Dunarea de Jos University of Galati, 35 AL Cuza St, 800010 Galati, Romania., Dragostin OM; Faculty of Medicine and Pharmacy, Dunarea de Jos University of Galati, 35 AL Cuza St, 800010 Galati, Romania., Fulga A; Faculty of Medicine and Pharmacy, Dunarea de Jos University of Galati, 35 AL Cuza St, 800010 Galati, Romania., Nechita L; Faculty of Medicine and Pharmacy, Dunarea de Jos University of Galati, 35 AL Cuza St, 800010 Galati, Romania., Ciubara AB; Faculty of Medicine and Pharmacy, Dunarea de Jos University of Galati, 35 AL Cuza St, 800010 Galati, Romania., Piraianu AI; Faculty of Medicine and Pharmacy, Dunarea de Jos University of Galati, 35 AL Cuza St, 800010 Galati, Romania., Stamate E; Department of Cardiology, University Emergency Hospital of Bucharest, 169 Splaiul Independentei St, 050098 Bucharest, Romania.; Faculty of Medicine and Pharmacy, Dunarea de Jos University of Galati, 35 AL Cuza St, 800010 Galati, Romania., Poalelungi DG; Faculty of Medicine and Pharmacy, Dunarea de Jos University of Galati, 35 AL Cuza St, 800010 Galati, Romania., Dragostin I; Emergency County Clinical Hospital, 2 Buzaului St, 810325 Braila, Romania., Iancu DC; Saint Apostle Andrew Emergency County Clinical Hospital, 177 Brailei St, 800578 Galati, Romania., Ciubara A; Faculty of Medicine and Pharmacy, Dunarea de Jos University of Galati, 35 AL Cuza St, 800010 Galati, Romania., Fulga I; Faculty of Medicine and Pharmacy, Dunarea de Jos University of Galati, 35 AL Cuza St, 800010 Galati, Romania. |
| Abstrakt: |
Cardiovascular diseases (CVDs) are the leading cause of premature death and disability globally, leading to significant increases in healthcare costs and economic strains. Artificial intelligence (AI) is emerging as a crucial technology in this context, promising to have a significant impact on the management of CVDs. A wide range of methods can be used to develop effective models for medical applications, encompassing everything from predicting and diagnosing diseases to determining the most suitable treatment for individual patients. This literature review synthesizes findings from multiple studies that apply AI technologies such as machine learning algorithms and neural networks to electrocardiograms, echocardiography, coronary angiography, computed tomography, and cardiac magnetic resonance imaging. A narrative review of 127 articles identified 31 papers that were directly relevant to the research, encompassing a broad spectrum of AI applications in cardiology. These applications included AI models for ECG, echocardiography, coronary angiography, computed tomography, and cardiac MRI aimed at diagnosing various cardiovascular diseases such as coronary artery disease, hypertrophic cardiomyopathy, arrhythmias, pulmonary embolism, and valvulopathies. The papers also explored new methods for cardiovascular risk assessment, automated measurements, and optimizing treatment strategies, demonstrating the benefits of AI technologies in cardiology. In conclusion, the integration of artificial intelligence (AI) in cardiology promises substantial advancements in diagnosing and treating cardiovascular diseases. |
