Cardiovascular Institute, Warren Alpert Medical School at Brown University, Providence, Rhode Island.
Division of Cardiovascular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts.
JACC Cardiovasc Interv. 2019 Jul 22;12(14):1293-1303. doi: 10.1016/j.jcin.2019.04.048.
Access to big data analyzed by supercomputers using advanced mathematical algorithms (i.e., deep machine learning) has allowed for enhancement of cognitive output (i.e., visual imaging interpretation) to previously unseen levels and promises to fundamentally change the practice of medicine. This field, known as "artificial intelligence" (AI), is making significant progress in areas such as automated clinical decision making, medical imaging analysis, and interventional procedures, and has the potential to dramatically influence the practice of interventional cardiology. The unique nature of interventional cardiology makes it an ideal target for the development of AI-based technologies designed to improve real-time clinical decision making, streamline workflow in the catheterization laboratory, and standardize catheter-based procedures through advanced robotics. This review provides an introduction to AI by highlighting its scope, potential applications, and limitations in interventional cardiology.
利用超级计算机和先进数学算法（即深度学习）分析大数据，使认知输出（即视觉成像解读）达到了前所未有的水平，并有望从根本上改变医学实践。这个领域被称为“人工智能”（AI），在自动化临床决策、医学成像分析和介入性手术等领域取得了显著进展，并有可能极大地影响介入心脏病学的实践。介入心脏病学的独特性质使其成为开发基于人工智能技术的理想目标，这些技术旨在通过先进的机器人技术来改善实时临床决策、简化导管实验室的工作流程并规范基于导管的程序。本综述通过强调人工智能在介入心脏病学中的范围、潜在应用和局限性，对其进行了介绍。
