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This study integrates the temporal convolutional network (TCN) and residual network (ResNet) frameworks to effectively classify atrial fibrillation in single-lead ECGs, thereby enhancing the application of neural networks in this field. Our model demonstrated significant success in detecting atrial fibrillation, with experimental results showing an accuracy rate of 97% and an F1 score of 87%. These figures indicate the model\u2019s exceptional performance in identifying both majority and minority classes, reflecting its balanced and accurate classification capability. This research offers new perspectives and tools for diagnosis and treatment in cardiology, grounded in advanced neural network technology.<\/jats:p>","DOI":"10.3390\/s24020398","type":"journal-article","created":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T09:43:24Z","timestamp":1704793404000},"page":"398","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Atrial Fibrillation Detection with Single-Lead Electrocardiogram Based on Temporal Convolutional Network\u2013ResNet"],"prefix":"10.3390","volume":"24","author":[{"given":"Xiangyu","family":"Zhao","sequence":"first","affiliation":[{"name":"ShenSi Lab, Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Chengdu 518110, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8527-0020","authenticated-orcid":false,"given":"Rong","family":"Zhou","sequence":"additional","affiliation":[{"name":"ShenSi Lab, Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Chengdu 518110, China"},{"name":"National Supercomputing Center in Shenzhen, Shenzhen 518005, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Ning","sequence":"additional","affiliation":[{"name":"ShenSi Lab, Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Chengdu 518110, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiuquan","family":"Guo","sequence":"additional","affiliation":[{"name":"ShenSi Lab, Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Chengdu 518110, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Liang","sequence":"additional","affiliation":[{"name":"ShenSi Lab, Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Chengdu 518110, China"},{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Yang","sequence":"additional","affiliation":[{"name":"ShenSi Lab, Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, Chengdu 518110, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"956","DOI":"10.1016\/j.bspc.2013.10.008","article-title":"Advances in modeling and characterization of atrial arrhythmias","volume":"8","author":"Rieta","year":"2013","journal-title":"Biomed. 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