医学
背景(考古学)
冠状动脉疾病
心脏病学
内科学
介入心脏病学
叙述性评论
肺栓塞
肥厚性心肌病
重症监护医学
放射科
人工智能
计算机科学
古生物学
生物
作者
Octavian Stefan Patrascanu,Dana Tutunaru,Carmina Liana Mușat,Oana Maria Dragostin,Ana Fulga,Luiza Nechita,Alexandru Bogdan Ciubară,Alin Ionut Piraianu,Elena Stamate,Diana Gina Poalelungi,Ionuţ Dragostin,Doriana Iancu,Anamaria Ciubară,Iuliu Fulga
摘要
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.
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