Artificial intelligence to detect abnormal heart rhythm from scanned electrocardiogram tracings

BACKGROUND: Electrocardiogram (ECG) interpretation is an integral part of the clinical ECG workflow; however, this process is often time‐consuming and labor‐intensive. We aim to develop a rapid, inexpensive means to detect abnormal ECGs using artificial intelligence (AI) from scanned ECG printouts....

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Detalles Bibliográficos
Autores principales: Bridge, Joshua, Fu, Lu, Lin, Weidong, Xue, Yumei, Lip, Gregory Y. H., Zheng, Yalin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237304/
https://www.ncbi.nlm.nih.gov/pubmed/35785392
http://dx.doi.org/10.1002/joa3.12707

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237304/
https://www.ncbi.nlm.nih.gov/pubmed/35785392
http://dx.doi.org/10.1002/joa3.12707

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