Artificial intelligence predicts clinically relevant atrial high-rate episodes in patients with cardiac implantable electronic devices

To assess the utility of machine learning (ML) algorithms in predicting clinically relevant atrial high-rate episodes (AHREs), which can be recorded by a pacemaker. We aimed to develop ML-based models to predict clinically relevant AHREs based on the clinical parameters of patients with implanted pa...

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Detalles Bibliográficos
Autores principales: Kim, Min, Kang, Younghyun, You, Seng Chan, Park, Hyung-Deuk, Lee, Sang-Soo, Kim, Tae-Hoon, Yu, Hee Tae, Choi, Eue-Keun, Park, Hyoung-Seob, Park, Junbeom, Lee, Young Soo, Kang, Ki-Woon, Shim, Jaemin, Sung, Jung-Hoon, Oh, Il-Young, Park, Jong Sung, Joung, Boyoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8741914/
https://www.ncbi.nlm.nih.gov/pubmed/34996990
http://dx.doi.org/10.1038/s41598-021-03914-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8741914/
https://www.ncbi.nlm.nih.gov/pubmed/34996990
http://dx.doi.org/10.1038/s41598-021-03914-4

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