Cross-site transportability of an explainable artificial intelligence model for acute kidney injury prediction

Artificial intelligence (AI) has demonstrated promise in predicting acutekidney injury (AKI), however, clinical adoption of these models requires interpretability and transportability across sites. Here, the authors develop an AKI prediction model and a measure for model transportability across six...

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Autores principales: Xing Song, Alan S. L. Yu, John A. Kellum, Lemuel R. Waitman, Michael E. Matheny, Steven Q. Simpson, Yong Hu, Mei Liu
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/54f7a10e954145e38407819c041b1309
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