Deep learning survival model for colorectal cancer patients (DeepCRC) with Asian clinical data compared with different theories

Abstract

IntroductionColorectal 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.Material and methodsWe conducted 8 NN survival models of CRC (n = 416) with different theories and compared them using Asian data.ResultsDeepSurv performed best with a C-index value of 0.8300 in the training cohort and 0.7681 in the test cohort.ConclusionsThe deep learning survival model for CRC patients (DeepCRC) could predict CRC’s OS accurately.