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Echocardiography-based AI detection of regional wall motion abnormalities and quantification of cardiac function in myocardial infarction
OBJECTIVE: To compare the performance of a newly developed deep learning (DL) framework for automatic detection of regional wall motion abnormalities (RWMAs) for patients presenting with the suspicion of myocardial infarction from echocardiograms obtained with portable bedside equipment versus stand...
Autores principales: | Lin, Xixiang, Yang, Feifei, Chen, Yixin, Chen, Xiaotian, Wang, Wenjun, Chen, Xu, Wang, Qiushuang, Zhang, Liwei, Guo, Huayuan, Liu, Bohan, Yu, Liheng, Pu, Haitao, Zhang, Peifang, Wu, Zhenzhou, Li, Xin, Burkhoff, Daniel, He, Kunlun |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441592/ https://www.ncbi.nlm.nih.gov/pubmed/36072864 http://dx.doi.org/10.3389/fcvm.2022.903660 |
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