Division of Cardiac Surgery, Department of Cardiothoracic Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania.
Ann Thorac Surg. 2020 May;109(5):1323-1329. doi: 10.1016/j.athoracsur.2019.09.042. Epub 2019 Nov 7.
This review article provides an overview of artificial intelligence (AI) and machine learning (ML) as it relates to cardiovascular health care.
An overview of the terminology and algorithms used in ML as it relates to health care are provided by the author. Articles published up to August 1, 2019, in the field of AI and ML in cardiovascular medicine are also reviewed and placed in the context of the potential role these approaches will have in clinical practice in the future.
AI is a broader term referring to the ability of machines to perform intelligent tasks, and ML is a subset of AI that refers to the ability of machines to learn independently and make accurate predictions. An expanding body of literature has been published using ML in cardiovascular health care. Moreover, ML has been applied in the settings of automated imaging interpretation, natural language processing and data extraction from electronic health records, and predictive analytics. Examples include automated interpretation of chest roentgenograms, electrocardiograms, echocardiograms, and angiography; identification of patients with early heart failure using clinical notes evaluated by ML; and predicting mortality or complications following percutaneous or surgical cardiovascular procedures.
Although there is an expanding body of literature on AI and ML in cardiovascular medicine, the future these fields will have in clinical practice remains to be paved. In particular, there is a promising role in providing automated imaging interpretation, automated data extraction and quality control, and clinical risk prediction, although these techniques require further refinement and evaluation.
本文综述了人工智能（AI）和机器学习（ML）在心血管保健方面的应用。
作者概述了 ML 在医疗保健领域中使用的术语和算法。还回顾了截至 2019 年 8 月 1 日发表的关于心血管医学中 AI 和 ML 的文章，并将其置于这些方法在未来临床实践中可能发挥作用的背景下。
AI 是一个更广泛的术语，指的是机器执行智能任务的能力，而 ML 是 AI 的一个子集，指的是机器独立学习和做出准确预测的能力。越来越多的文献使用 ML 来进行心血管保健。此外，ML 已应用于自动图像解释、自然语言处理和电子健康记录中的数据提取以及预测分析。例如，自动解释胸部 X 光片、心电图、超声心动图和血管造影；使用 ML 评估临床笔记来识别早期心力衰竭患者；以及预测经皮或手术心血管手术后的死亡率或并发症。
尽管在心血管医学中 AI 和 ML 的文献不断增加，但这些领域在临床实践中的未来仍有待开拓。特别是在提供自动图像解释、自动数据提取和质量控制以及临床风险预测方面，具有广阔的前景，尽管这些技术需要进一步的改进和评估。
