Characterizing arrhythmia using machine learning analysis of Ca(2+) cycling in human cardiomyocytes

Accurate modeling of the heart electrophysiology to predict arrhythmia susceptibility remains a challenge. Current electrophysiological analyses are hypothesis-driven models drawing conclusions from changes in a small subset of electrophysiological parameters because of the difficulty of handling an...

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Detalles Bibliográficos
Autores principales: Pang, Jeremy K.S., Chia, Sabrina, Zhang, Jinqiu, Szyniarowski, Piotr, Stewart, Colin, Yang, Henry, Chan, Woon-Khiong, Ng, Shi Yan, Soh, Boon-Seng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9391413/
https://www.ncbi.nlm.nih.gov/pubmed/35839773
http://dx.doi.org/10.1016/j.stemcr.2022.06.005

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9391413/
https://www.ncbi.nlm.nih.gov/pubmed/35839773
http://dx.doi.org/10.1016/j.stemcr.2022.06.005

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