Ontology highlight
ABSTRACT:
SUBMITTER: Song X
PROVIDER: S-EPMC7653032 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
Nature communications 20201109 1
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 PCORnet platform to develop an AKI prediction model and assess its transportability across six independent health systems. Our work demonstrates that cross-site performance deterioration is likely and re ...[more]