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Development and validation of an interpretable neural network for prediction of postoperative in-hospital mortality
While deep neural networks (DNNs) and other machine learning models often have higher accuracy than simpler models like logistic regression (LR), they are often considered to be “black box” models and this lack of interpretability and transparency is considered a challenge for clinical adoption. In...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794438/ https://www.ncbi.nlm.nih.gov/pubmed/33420341 http://dx.doi.org/10.1038/s41746-020-00377-1 |