基于人工智能的单导联心电图用于缺血性心脏病的早期检测
Artificial intelligence-enabled single-lead electrocardiogram in early detection of ischemic heart disease.
作者信息
Song Wen-Hua, Tse Gary, Chen Kang-Yin, Liu Tong
机构信息
Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, The Second Hospital of Tianjin Medical University, Tianjin 300211, China.
School of Nursing and Health Sciences, Hong Kong Metropolitan University, Hong Kong 999077, China.
出版信息
World J Cardiol. 2025 Jul 26;17(7):108510. doi: 10.4330/wjc.v17.i7.108510.
With the rapid advancement and widespread adoption of new artificial intelligence (AI) technologies, personalized medicine and more accurate diagnosis using medical imaging are now possible. Among its many applications, AI has shown remarkable potential in the analysis of electrocardiograms (ECGs), which provide essential insights into the electrical activity of the heart and allowing early detection of ischemic heart disease (IHD). Notably, single-lead ECG (SLECG) analysis has emerged as a key focus in recent research due to its potential for widespread and efficient screening. This editorial focuses on the latest research progress of AI-enabled SLECG utilized in the diagnosis of IHD.
随着新人工智能（AI）技术的迅速发展和广泛应用，利用医学成像实现个性化医疗和更准确的诊断如今已成为可能。在其众多应用中，AI在心电图（ECG）分析方面展现出了显著潜力，心电图能够提供有关心脏电活动的重要信息，并有助于早期检测缺血性心脏病（IHD）。值得注意的是，单导联心电图（SLECG）分析因其具有广泛且高效筛查的潜力，已成为近期研究的一个关键重点。这篇社论聚焦于用于IHD诊断的人工智能辅助SLECG的最新研究进展。
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