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Using model explanations to guide deep learning models towards consistent explanations for EHR data
It has been shown that identical deep learning (DL) architectures will produce distinct explanations when trained with different hyperparameters that are orthogonal to the task (e.g. random seed, training set order). In domains such as healthcare and finance, where transparency and explainability is...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674624/ https://www.ncbi.nlm.nih.gov/pubmed/36400825 http://dx.doi.org/10.1038/s41598-022-24356-6 |