Development and Validation of a Deep Learning Model for Non-Small Cell Lung Cancer Survival.

ABSTRACT:

Importance

There is a lack of studies exploring the performance of a deep learning survival neural network in non-small cell lung cancer (NSCLC).

Objectives

To compare the performances of DeepSurv, a deep learning survival neural network with a tumor, node, and metastasis staging system in the prediction of survival and test the reliability of individual treatment recommendations provided by the deep learning survival neural network.

Design, setting, and participants

In this population-based cohort study, a deep learning-based algorithm was developed and validated using consecutive cases of newly diagnosed stages I to IV NSCLC between January 2010 and December 2015 in a Surveillance, Epidemiology, and End Results database. A total of 127 features, including patient ch

SUBMITTER: She Y 

PROVIDER: S-EPMC7272121 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature