There has been a tidal wave of recent interest in artificial intelligence (AI), machine learning and deep learning approaches in cardiovascular (CV) medicine. In the era of modern medicine, AI and electronic health records hold the promise to improve the understanding of disease conditions and bring a personalized approach to CV care. The field of CV imaging (CVI), incorporating echocardiography, cardiac computed tomography, cardiac magnetic resonance imaging and nuclear imaging, with sophisticated imaging techniques and high volumes of imaging data, is primed to be at the forefront of the revolution in precision cardiology. This review provides a contemporary overview of the CVI imaging applications of AI, including a critique of the strengths and potential limitations of deep learning approaches.

最近对人工智能（AI），机器学习和心血管（CV）医学的深度学习方法产生了浓厚的兴趣。在现代医学时代，人工智能和电子健康记录有望改善人们对疾病状况的了解，并为CV护理带来个性化的方法。CV成像（CVI）领域，结合了超声心动图，心脏计算机断层扫描，心脏磁共振成像和核成像，以及先进的成像技术和大量成像数据，已注定将成为精确心脏病学革命的前沿。这篇评论提供了AI的CVI成像应用的当代概述，包括对深度学习方法的优势和潜在局限性的批评。