Nature Communications (Nov 2020)

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

  • Xing Song,
  • Alan S. L. Yu,
  • John A. Kellum,
  • Lemuel R. Waitman,
  • Michael E. Matheny,
  • Steven Q. Simpson,
  • Yong Hu,
  • Mei Liu

DOI
https://doi.org/10.1038/s41467-020-19551-w
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 12

Abstract

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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 independent health systems.