Deep Learning-Based Death Prediction Model for Chronic Kidney Disease

This study identified emergency visits and prolonged hospital stays as key predictors of death in CKD patients. To mitigate these risks, regular monitoring by nephrology specialists and timely initiation of renal replacement therapy are essential. Age also emerged as a critical determinant, emphasizing the importance of age-stratified clinical guidelines amid global aging trends. The high-performing, simplified predictive model based on general characteristics offers a valuable tool for rapid prognosis assessment in primary and secondary healthcare settings.