Construction and validation of prognostic models for acute kidney disease and mortality in patients at risk of malnutrition: an interpretable machine learning approach

The LGBM models provide an effective method for predicting AKD, AKI and mortality at an early stage in patients at risk of malnutrition, enabling prompt interventions. Compared with the AKD model, the models for predicting AKI and mortality perform better. The AI-driven web application can significantly aid in creating personalized preventive measures. Future work will aim to expand the application to larger, more diverse populations, incorporate additional biomarkers and refine ML algorithms to improve predictive accuracy and clinical utility.