Localization of myocardial infarction using a multi-branch weight sharing network based on 2-D vectorcardiogram
文献类型：期刊论文
| 作者 | He, Cong3,4; Liu, Ming4 ; Xiong, Peng4; Yang, Jianli4; Du, Haiman4; Xu, Jinpeng2; Hou, Zengguang1; Liu, Xiuling4
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| 刊名 | ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
 |
| 出版日期 | 2022-11-01 |
| 卷号 | 116页码:9 |
| 关键词 | Vectorcardiogram Myocardial infarction Multi-branch neural network Weight sharing |
| ISSN号 | 0952-1976 |
| DOI | 10.1016/j.engappai.2022.105428 |
| 通讯作者 | Liu, Xiuling(liuxiuling121@hotmail.comm) |
| 英文摘要 | Early diagnosis and localization of myocardial infarction (MI) assist clinicians in saving numerous lives through the timely treatment for patients with MI. Vectorcardiogram (VCG) can reflect the characteristic changes of cardiac electrical activity in MI in detail. In this context, the present study reports a multi-branch weight sharing network model based on 2-D VCG constructed to realize the automatic localization of MI. The three -branch network extracted the spatial morphological features of the three planes of the 2-D VCG, respectively, and the weight-sharing part of the network obtained the spatial correlation information among the three planes. Subsequently, the Softmax classifier was employed to classify normal individuals and MI patients (11 class infarct sites). To evaluate the performance of the proposed method for MI localization, PTB(Physikalisch-Technische Bundesanstalt) diagnostic ECG database was employed. The localization accuracy, sensitivity, and specificity achieved using the proposed method were 99.87%, 99.92%, and 99.99%, respectively. Thus, the proposed scheme is expected to be useful in assisting cardiologists in interpreting VCG for clinical diagnosis. |
| WOS关键词 | ECG ; DYNAMICS |
| 资助项目 | National Natural Science Foundation of China ; Nat-ural Science Foundation of Hebei Province ; Youth Talent Support Program of Hebei Province ; Science and Technology Research Project of Higher Education Institution of Hebei Province ; Key project of Science and Technol-ogy for Higher Education Institutions in Hebei Province ; [U20A20224] ; [62006067] ; [F2021201008] ; [BJ2019044] ; [QN2020428] ; [ZD2021013] |
| WOS研究方向 | Automation & Control Systems ; Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000876457200011 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 资助机构 | National Natural Science Foundation of China ; Nat-ural Science Foundation of Hebei Province ; Youth Talent Support Program of Hebei Province ; Science and Technology Research Project of Higher Education Institution of Hebei Province ; Key project of Science and Technol-ogy for Higher Education Institutions in Hebei Province |
| 源URL | [http://ir.ia.ac.cn/handle/173211/50669]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
| 通讯作者 | Liu, Xiuling |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Hebei Univ, Affiliated Hosp, Baoding 071002, Peoples R China 3.Hebei Univ, Sch Qual & Tech Supervis, Baoding 071002, Peoples R China 4.Hebei Univ, Coll Elect & Informat Engn, Key Lab Digital Med Engn Hebei Prov, Baoding 071002, Peoples R China |
| 推荐引用方式 GB/T 7714 | He, Cong,Liu, Ming,Xiong, Peng,et al. Localization of myocardial infarction using a multi-branch weight sharing network based on 2-D vectorcardiogram[J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,2022,116:9. |
| APA | He, Cong.,Liu, Ming.,Xiong, Peng.,Yang, Jianli.,Du, Haiman.,...&Liu, Xiuling.(2022).Localization of myocardial infarction using a multi-branch weight sharing network based on 2-D vectorcardiogram.ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,116,9. |
| MLA | He, Cong,et al."Localization of myocardial infarction using a multi-branch weight sharing network based on 2-D vectorcardiogram".ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 116(2022):9. |
入库方式： OAI收割
来源：自动化研究所
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