Abstract
INTRODUCTION: Colorectal cancer (CRC) is the third most common cancer. Precise prediction of CRC patients' overall survival (OS) probability could offer advice on its treatment. Neural network (NN) is the first-class algorithm, but a consensus on which NN survival models are better has not been established yet. A predictive model on CRC using Asian data is also lacking. METHODS: We conducted 8 NN survival models of CRC (n = 416) with different theories and compared them using Asian data. RESULTS: DeepSurv performed best with a C-index value of 0.8300 in the training cohort and 0.7681 in the test cohort. CONCLUSIONS: The deep learning survival model for CRC patients (DeepCRC) could predict CRC's OS accurately.