Learning to predict in-hospital mortality risk in the intensive care unit with attention-based temporal convolution network

BACKGROUND: Dynamic prediction of patient mortality risk in the ICU with time series data is limited due to high dimensionality, uncertainty in sampling intervals, and other issues. A new deep learning method, temporal convolution network (TCN), makes it possible to deal with complex clinical time s...

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Detalles Bibliográficos
Autores principales: Chen, Yu-wen, Li, Yu-jie, Deng, Peng, Yang, Zhi-yong, Zhong, Kun-hua, Zhang, Li-ge, Chen, Yang, Zhi, Hong-yu, Hu, Xiao-yan, Gu, Jian-teng, Ning, Jiao-lin, Lu, Kai-zhi, Zhang, Ju, Xia, Zheng-yuan, Qin, Xiao-lin, Yi, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034533/
https://www.ncbi.nlm.nih.gov/pubmed/35461225
http://dx.doi.org/10.1186/s12871-022-01625-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034533/
https://www.ncbi.nlm.nih.gov/pubmed/35461225
http://dx.doi.org/10.1186/s12871-022-01625-5

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