Artificial intelligence algorithm for predicting cardiac arrest using electrocardiography

BACKGROUND: In-hospital cardiac arrest is a major burden in health care. Although several track-and-trigger systems are used to predict cardiac arrest, they often have unsatisfactory performances. We hypothesized that a deep-learning-based artificial intelligence algorithm (DLA) could effectively pr...

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Detalles Bibliográficos
Autores principales: Kwon, Joon-myoung, Kim, Kyung-Hee, Jeon, Ki-Hyun, Lee, Soo Youn, Park, Jinsik, Oh, Byung-Hee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7541213/
https://www.ncbi.nlm.nih.gov/pubmed/33023615
http://dx.doi.org/10.1186/s13049-020-00791-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7541213/
https://www.ncbi.nlm.nih.gov/pubmed/33023615
http://dx.doi.org/10.1186/s13049-020-00791-0

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