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- Wei Li, Shuye Lin, Yuqi He, Jinghui Wang, and Yuanming Pan.
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Tongzhou District, Beijing, China.
- Arch Med Sci. 2023 Jan 1; 19 (1): 264269264-269.
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.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.Copyright: © 2022 Termedia & Banach.
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