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Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk
To compare different deep learning architectures for predicting the risk of readmission within 30 days of discharge from the intensive care unit (ICU). The interpretability of attention-based models is leveraged to describe patients-at-risk. Several deep learning architectures making use of attentio...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6981230/ https://www.ncbi.nlm.nih.gov/pubmed/31980704 http://dx.doi.org/10.1038/s41598-020-58053-z |