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本文引用的文献

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Rev Port Cardiol. 2023 Jul;42(7):643-651. doi: 10.1016/j.repc.2023.03.016. Epub 2023 Mar 30.
3
Non-invasive detection of cardiac allograft rejection among heart transplant recipients using an electrocardiogram based deep learning model.使用基于心电图的深度学习模型对心脏移植受者进行心脏移植排斥反应的无创检测。
Eur Heart J Digit Health. 2023 Jan 13;4(2):71-80. doi: 10.1093/ehjdh/ztad001. eCollection 2023 Mar.
4
An Artificial Intelligence-Enabled ECG Algorithm for Predicting the Risk of Recurrence in Patients with Paroxysmal Atrial Fibrillation after Catheter Ablation.一种用于预测阵发性心房颤动患者导管消融术后复发风险的人工智能心电图算法
J Clin Med. 2023 Mar 1;12(5):1933. doi: 10.3390/jcm12051933.
5
ECG signal feature extraction trends in methods and applications.心电图信号特征提取方法及应用的研究进展。
Biomed Eng Online. 2023 Mar 8;22(1):22. doi: 10.1186/s12938-023-01075-1.
6
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人工智能在数字心电图中还能看到什么?

What Else Can AI See in a Digital ECG?

作者信息

Rechciński Tomasz

机构信息

Chair and Department of Cardiology, Medical University of Lodz, 91-347 Lodz, Poland.

出版信息

J Pers Med. 2023 Jun 28;13(7):1059. doi: 10.3390/jpm13071059.

DOI:10.3390/jpm13071059
PMID:37511672
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10381961/
Abstract

The electrocardiogram (ECG), considered by some diagnosticians of cardiovascular diseases to be a slightly anachronistic tool, has acquired a completely new face and importance thanks to its three modern features: the digital form of recording, its very frequent use, and the possibility of processing thousands of records by artificial intelligence (AI). In this review of the literature on this subject from the first 3 months of 2023, the use of many types of software for extracting new information from the ECG is described. These include, among others, natural language processing, backpropagation neural network and convolutional neural network. AI tools of this type allow physicians to achieve high accuracy not only in ECG-based predictions of the patient's age or sex but also of the abnormal structure of heart valves, abnormal electrical activity of the atria, distorted immune response after transplantation, good response to resynchronization therapy and an increased risk of sudden cardiac death. The attractiveness of the presented results lies in the simplicity of the examination by the staff, relatively low costs and even the possibility of performing the examination remotely. The twelve studies presented here are just a fraction of the novelties that the current year will bring.

摘要

心电图(ECG),在一些心血管疾病诊断专家看来是一种略显过时的工具,但由于其三个现代特征——数字化记录形式、频繁使用以及借助人工智能(AI)处理数千份记录的可能性,它已呈现出全新的面貌并具有了新的重要性。在这篇对2023年前三个月关于该主题的文献综述中,描述了使用多种软件从心电图中提取新信息的情况。其中包括自然语言处理、反向传播神经网络和卷积神经网络等。这类人工智能工具不仅能让医生在基于心电图预测患者年龄或性别方面,还能在预测心脏瓣膜异常结构、心房异常电活动、移植后免疫反应失调、对再同步治疗的良好反应以及心脏性猝死风险增加等方面达到高精度。所呈现结果的吸引力在于工作人员检查的简便性、相对较低的成本,甚至还能远程进行检查。这里展示的十二项研究只是今年即将带来的众多新成果的一小部分。