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...

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Detalles Bibliográficos
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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Cardiovascular Medicine
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

Internet

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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