Comparison of machine learning and logistic regression models in predicting acute kidney injury: A systematic review and meta-analysis
274 Citations•2021•
Xuan Song, Xinyan Liu, Fei Liu
Assessment of machine learning models at predicting acute kidney injury (AKI) suggests that ML models perform equally to that of LR, however ML models exhibit variable performance with some ML models displaying exceptional performance.
Abstract
These data suggest that ML models perform equally to that of LR, however ML models exhibit variable performance with some ML models displaying exceptional performance. The variability in ML prediction of AKI can be attributed, in part, to the specific ML model utilized, variable selection and processing, study and subject characteristics, and the steps associated with model training, validation, testing, and calibration.