血浆微小 RNA-223(miR-223)及叉头框蛋白3a水平与冠心病病人心脏结构变化的相关性研究

人工智能在心电图中的应用是心血管领域正在发生变革的一个重要方向。近年来，先进的人工智能技术，如深度学习，卷积神经网络等，已经实现了对心电图的快速、类似于人类的判读，而多层神经网络可以精确地检测到人类判读者基本无法识别的信号和模式，使心电图成为一个强大的“生物标志物”。大量的数字化心电图已经被用于开发人工智能模型，可检测阵发性心房颤动、左心室功能障碍、心肌病以及高钾血症、瓣膜疾病等异常情况。在这篇综述中，我们总结了人工智能辅助的心电图诊断在心血管疾病中的应用现状，讨论并评估了其临床意义、局限性和发展前景。

Correlation between plasma micro-223 (mir-223) and Forkhead Box 3a levels and cardiac structural changes in coronary heart disease patients

The application of artificial intelligence (AI) in the field of cardiovascular medicine is opening the future. Recently, advanced artificial intelligence technologies, including deep learning and convolutional neural network, have already performed rapid, human-like interpretations of electrocardiogram (ECG), some deep learning networks can even detect signals and models beyond human readers, making ECG a powerful biomarker. Large amounts of AI models have been developed for the detection of silent atrial fibrillation, left ventricular dysfunction, cardiomyopathy, hyperkalemia, valve disorders, and other phenotypes. In this review, we conclude the current state of the AI-enhanced ECG in the detection of cardiovascular diseases, discuss its clinical implications, potential limitations, and future developments.