{"title":"人工智能单导联心电图在缺血性心脏病早期检测中的应用。","authors":"Wen-Hua Song, Gary Tse, Kang-Yin Chen, Tong Liu","doi":"10.4330/wjc.v17.i7.108510","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":23800,"journal":{"name":"World Journal of Cardiology","volume":"17 7","pages":"108510"},"PeriodicalIF":2.8000,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12304860/pdf/","citationCount":"0","resultStr":"{\"title\":\"Artificial intelligence-enabled single-lead electrocardiogram in early detection of ischemic heart disease.\",\"authors\":\"Wen-Hua Song, Gary Tse, Kang-Yin Chen, Tong Liu\",\"doi\":\"10.4330/wjc.v17.i7.108510\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":23800,\"journal\":{\"name\":\"World Journal of Cardiology\",\"volume\":\"17 7\",\"pages\":\"108510\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2025-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12304860/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"World Journal of Cardiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4330/wjc.v17.i7.108510\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Journal of Cardiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4330/wjc.v17.i7.108510","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Artificial intelligence-enabled single-lead electrocardiogram in early detection of ischemic heart disease.
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.