West Virginia University Heart & Vascular Institute, 1 Medical Center Drive, Morgantown, WV, 26506, USA.
Curr Cardiol Rep. 2020 Jul 30;22(9):99. doi: 10.1007/s11886-020-01329-7.
Echocardiography is an indispensable tool in diagnostic cardiology and is fundamental to clinical care. Significant advances in cardiovascular imaging technology paralleled by rapid growth in electronic medical records, miniaturized devices, real-time monitoring, and wearable devices using body sensor network technology have led to the development of complex data.
The intricate nature of these data can be overwhelming and exceed the capabilities of current statistical software. Machine learning (ML), a branch of artificial intelligence (AI), can help health care providers navigate through this complex labyrinth of information and unravel hidden discoveries. Furthermore, ML algorithms can help automate several tasks in echocardiography and clinical care. ML can serve as a valuable diagnostic tool for physicians in the field of echocardiography. In addition, it can help expand the capabilities of research and discover alternative pathways in medical management. In this review article, we describe the role of AI and ML in echocardiography.
超声心动图是诊断心脏病学中不可或缺的工具，也是临床治疗的基础。心血管成像技术的重大进展，伴随着电子病历、小型化设备、实时监测以及使用身体传感器网络技术的可穿戴设备的快速增长，导致了复杂数据的出现。
这些数据的复杂性可能令人难以承受，超出了当前统计软件的能力。机器学习（ML）是人工智能（AI）的一个分支，可以帮助医疗保健提供者在这个复杂的信息迷宫中导航，并揭示隐藏的发现。此外，ML 算法可以帮助自动化超声心动图和临床护理中的几个任务。ML 可以作为超声心动图领域医生的有价值的诊断工具。此外，它可以帮助扩大研究能力，并发现医疗管理中的替代途径。在这篇综述文章中，我们描述了 AI 和 ML 在超声心动图中的作用。
