Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA; Demoulas Center for Cardiac Arrhythmias, Cardiology Division, Massachusetts General Hospital, Boston, MA, USA; Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
J Electrocardiol. 2023 Nov-Dec;81:142-145. doi: 10.1016/j.jelectrocard.2023.08.014. Epub 2023 Sep 4.
The 12‑lead electrocardiogram (ECG) is a common and inexpensive diagnostic modality available at scale. The ECG reflects electrical activity throughout the cardiac cycle and is increasingly recognized to contain rich signal relevant across the spectrum of human conditions. Recent work has demonstrated that artificial intelligence (AI)-based algorithms may be able to extract latent information from within the 12‑lead ECG to classify the presence of disease and even predict the development of future disease. Despite recent development of many AI-based ECG algorithms, comparably few are used in routine clinical practice. Therefore, there is a critical unmet need to identify and mitigate potential barriers to the real-world clinical implementation of AI algorithms. We propose that the adoption of the AI-enabled ECG may be increased by future efforts focused on three key principles: a) maximizing credibility, b) optimizing practicality, and c) establishing clinical utility. In this mini-review, we discuss recent notable work focused on these principles and provide suggestions for future directions. AI-enabled ECG analysis possesses substantial potential to transform current methods to prevent, diagnose, and treat human disease, but a greater emphasis on their real-world application is required to bring that potential to reality.
12 导联心电图（ECG）是一种常见且廉价的诊断方式，具有广泛的应用。心电图反映了整个心脏周期的电活动，并且越来越被认为包含了丰富的与人类各种状况相关的信号。最近的研究表明，基于人工智能（AI）的算法可能能够从 12 导联 ECG 中提取潜在信息，以对疾病的存在进行分类，甚至预测未来疾病的发展。尽管最近开发了许多基于 AI 的 ECG 算法，但在常规临床实践中使用的却相对较少。因此，迫切需要确定并减轻人工智能算法在现实世界临床应用中的潜在障碍。我们提出，未来可以通过以下三个关键原则来提高 AI 心电图的应用：a）最大化可信度，b）优化实用性，c）建立临床有效性。在本篇小型综述中，我们讨论了这些原则方面的最近的显著研究工作，并为未来的方向提供了建议。AI 心电图分析具有极大的潜力来改变当前预防、诊断和治疗人类疾病的方法，但需要更加重视其在现实世界中的应用，才能将这一潜力变为现实。
