Interpretable and Continuous Prediction of Acute Kidney Injury in the Intensive Care [chapter]

Iacopo Vagliano, Oleksandra Lvova, Martijn C. Schut
2021 Studies in Health Technology and Informatics  
Acute kidney injury (AKI) is a common and potentially life-threatening condition, which often occurs in the intensive care unit. We propose a machine learning model based on recurrent neural networks to continuously predict AKI. We internally validated its predictive performance, both in terms of discrimination and calibration, and assessed its interpretability. Our model achieved good discrimination (AUC 0.80-0.94). Such a continuous model can support clinicians to promptly recognize and treat AKI patients and may improve their outcomes.
doi:10.3233/shti210129 pmid:34042714 fatcat:d7limuppu5dg7buvmzucku2ize