Artificial intelligence and echocardiography.
Artificial intelligence and echocardiography.
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DOI：
10.1530/erp-18-0056
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发表时间：
2018-12-01
影响因子：
6.3
通讯作者：
Leeson P
中科院分区：
文献类型：
--
作者：
Alsharqi M;Woodward WJ;Mumith JA;Markham DC;Upton R;Leeson P
超声心动图在心血管疾病的诊断和治疗中起着至关重要的作用。然而，解释在很大程度上仍然依赖于操作者的主观专业知识。因此，操作员之间的差异和经验可能导致不正确的诊断。人工智能（AI）技术为超声心动图提供了新的可能性，以生成准确，一致和自动化的超声心动图解释，从而潜在地降低人为错误的风险。在这篇综述中，我们讨论了与图像解释相关的人工智能子领域，称为机器学习，以及其增强超声心动图诊断性能的潜力。我们讨论了这些方法的最新应用和人工智能辅助解释超声心动图的未来方向。该研究表明，应用机器学习模型来提供与临床医生相当的快速，高度准确和一致的超声心动图评估是可行的。这些算法能够准确量化广泛的特征，例如心脏瓣膜病的严重程度或冠状动脉疾病患者的缺血负荷。然而，超声心动图的应用和使用仍处于起步阶段。目前正在进行研究，以完善各种方法并验证其在自动化、量化和诊断方面的用途。在临床超声心动图实践中广泛采用强大的人工智能工具应该遵循，并有可能为患者结局带来显著益处。
Echocardiography plays a crucial role in the diagnosis and management of cardiovascular disease. However, interpretation remains largely reliant on the subjective expertise of the operator. As a result inter-operator variability and experience can lead to incorrect diagnoses. Artificial intelligence (AI) technologies provide new possibilities for echocardiography to generate accurate, consistent and automated interpretation of echocardiograms, thus potentially reducing the risk of human error. In this review, we discuss a subfield of AI relevant to image interpretation, called machine learning, and its potential to enhance the diagnostic performance of echocardiography. We discuss recent applications of these methods and future directions for AI-assisted interpretation of echocardiograms. The research suggests it is feasible to apply machine learning models to provide rapid, highly accurate and consistent assessment of echocardiograms, comparable to clinicians. These algorithms are capable of accurately quantifying a wide range of features, such as the severity of valvular heart disease or the ischaemic burden in patients with coronary artery disease. However, the applications and their use are still in their infancy within the field of echocardiography. Research to refine methods and validate their use for automation, quantification and diagnosis are in progress. Widespread adoption of robust AI tools in clinical echocardiography practice should follow and have the potential to deliver significant benefits for patient outcome.