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Cross-site transportability of an explainable artificial intelligence model for acute kidney injury prediction
Artificial intelligence (AI) has demonstrated promise in predicting acute kidney injury (AKI), however, clinical adoption of these models requires interpretability and transportability. Non-interoperable data across hospitals is a major barrier to model transportability. Here, we leverage the US PCO...
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| Publicado no: | Nat Commun |
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| Main Authors: | , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Publishing Group UK
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7653032/ https://ncbi.nlm.nih.gov/pubmed/33168827 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-020-19551-w |
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