Development and validation of a deep learning model to predict survival of patients with esophageal cancer.

ABSTRACT:

Objective

To compare the performance of a deep learning survival network with the tumor, node, and metastasis (TNM) staging system in survival prediction and test the reliability of individual treatment recommendations provided by the network.

Methods

In this population-based cohort study, we developed and validated a deep learning survival model using consecutive cases of newly diagnosed stage I to IV esophageal cancer between January 2004 and December 2015 in a Surveillance, Epidemiology, and End Results (SEER) database. The model was externally validated in an independent cohort from Fujian Provincial Hospital. The C statistic was used to compare the performance of the deep learning survival model and TNM staging system. Two other deep learning risk prediction models were

SUBMITTER: Huang C 

PROVIDER: S-EPMC9399685 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature