Deep Learning-Based Emergency Care Process Reengineering of Interventional Data for Patients with Emergency Time-Series Events of Myocardial Infarction

This paper proposes a representation learning framework HE-LSTM model for heterogeneous temporal events, which can automatically adapt to the multiscale sampling frequency of multisource heterogeneous data. The proposed model also demonstrates its superiority over other typical approaches on real da...

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Detalles Bibliográficos
Autores principales: Gao, Na, Xu, Yue, Tu, Lili, Zhu, Siyue, Zhang, Shuhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8890826/
https://www.ncbi.nlm.nih.gov/pubmed/35251574
http://dx.doi.org/10.1155/2022/7339930

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8890826/
https://www.ncbi.nlm.nih.gov/pubmed/35251574
http://dx.doi.org/10.1155/2022/7339930

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