Transformer-based time-to-event prediction for chronic kidney disease deterioration
Transformer-based time-to-event prediction for chronic kidney disease deterioration
Abstract Objective Deep-learning techniques, particularly the Transformer model, have shown great potential in enhancing the prediction performance of longitudinal health records. Previous methods focused on fixed-time risk prediction, however, time-to-event prediction is often more appropriate for clinical scenarios. Here, we present STRAFE, a generalizable survival analysis Transformer-based architecture for electronic …