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Journal of Medical Signals and Sensors، جلد ۱۵، شماره ۱۰، صفحات ۱۰-۴۱۰۳
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عنوان انگلیسی A Deep Learning Approach Toward Differentiating Left versus Right for Idiopathic Ventricular Arrhythmia Originated from Outflow Tract
چکیده انگلیسی مقاله Abstract Background:  Idiopathic ventricular arrhythmia (VA) is among the common cardiac diseases, ranging from benign conditions to those requiring immediate medical intervention. Many VAs originate from the heart’s outflow tract (OT). However, this area’s complexity and small size, along with other influencing external factors, pose significant challenges to accurate diagnosis. The similarity of the features of VAs on the electrocardiogram (ECG) originating from the right or left side of the OT may lead to misdiagnosis. This study aims to detect the site of origin for VAs originating from the OT, which is important as a key precognition for treatment during catheter ablation. Methods:  We perform this diagnosis using the standard 12-lead ECG and deep learning (DL) techniques without additional equipment. First, inspired by next-generation sequencing in genetics, we created one-dimensional (1D) streams of premature beats from a public dataset of 334 patients. Then, to compare the performance of common 1D DL models, the data were presented to various models, including long short-term memory, gated recurrent unit, and 1D convolutional neural network (1D-CNN). Results:  Experimental results show that the 1D-CNN network achieves the best performance, with an accuracy of 93.4% and an F1-score of 0.9313. Conclusions:  The findings demonstrate the effectiveness of DL in a higher level of applications, specifically in the treatment process, compared to conventional ECG analysis applications based on computerized methods. This represents a promising prospect for use in treatment processes without relying on complex and multifaceted diagnostic methods in the future.
کلیدواژه‌های انگلیسی مقاله Catheter ablation,electrocardiogram,heart disease,idiopathic ventricular arrhythmia,left ventricular outflow tract,outflow tract,right ventricular outflow tract
نویسندگان مقاله | Reza Talebzadeh
Faculty of Electrical Engineering, Shahrood University of Technology, Shahrood, Iran


| Hossein Khosravi Khosravi
Department of Cardiac Electrophysiology, Rajaie Cardiovascular Medical and Research Institute, Iran University of Medical Sciences, Tehran, Iran


| Majid Haghjoo
3.Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Science, Tehran, Iran 4.Research Center for Biomedical Technologies and Robotics, Advanced Medical Technologies and Equipment Institute, Tehran University of Medical Sciences, IKHC Hospital, Tehran, Iran


| Bahador Makki Abadi


نشانی اینترنتی http://jmss.mui.ac.ir/index.php/jmss/article/view/765
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زبان مقاله منتشر شده en
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نوع مقاله منتشر شده Original Articles
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