Department of Medicine and Surgery, University of Milano-Bicocca; Milan-Italy.
1st Department of Cardiology, Poznan University of Medical Sciences; Poznan-Poland.
Anatol J Cardiol. 2020 Oct;24(4):214-223. doi: 10.14744/AnatolJCardiol.2020.94491.
Rapid development of artificial intelligence (AI) is gaining grounds in medicine. Its huge impact and inevitable necessity are also reflected in cardiovascular imaging. Although AI would probably never replace doctors, it can significantly support and improve their productivity and diagnostic performance. Many algorithms have already proven useful at all stages of the cardiac imaging chain. Their crucial practical applications include classification, automatic quantification, notification, diagnosis, and risk prediction. Consequently, more reproducible and repeatable studies are obtained, and personalized reports may be available to any patient. Utilization of AI also increases patient safety and decreases healthcare costs. Furthermore, AI is particularly useful for beginners in the field of cardiac imaging as it provides anatomic guidance and interpretation of complex imaging results. In contrast, lack of interpretability and explainability in AI carries a risk of harmful recommendations. This review was aimed at summarizing AI principles, essential execution requirements, and challenges as well as its recent applications in cardiovascular imaging.
人工智能（AI）在医学领域的发展迅速。它在心血管成像中的巨大影响和必要性也得到了体现。虽然 AI 可能永远不会取代医生，但它可以极大地支持和提高医生的工作效率和诊断水平。许多算法已经在心脏成像链的各个阶段证明了其有用性。其关键的实际应用包括分类、自动量化、通知、诊断和风险预测。因此，可以获得更具可重复性和可重复性的研究，并且可以为任何患者提供个性化的报告。AI 的使用还可以提高患者的安全性并降低医疗成本。此外，AI 对于心脏成像领域的初学者特别有用，因为它可以提供解剖指导和对复杂成像结果的解释。相比之下，AI 的缺乏可解释性和可说明性存在产生有害建议的风险。本综述旨在总结 AI 的原理、基本执行要求和挑战，以及其在心血管成像中的最新应用。
