A novel deep learning prognostic system improves survival predictions for stage III non-small cell lung cancer.

ABSTRACT:

Background

Accurate prognostic prediction plays a crucial role in the clinical setting. However, the TNM staging system fails to provide satisfactory individual survival prediction for stage III non-small cell lung cancer (NSCLC). The performance of the deep learning network for survival prediction in stage III NSCLC has not been explored.

Objectives

This study aimed to develop a deep learning-based prognostic system that could achieve better predictive performance than the existing staging system for stage III NSCLC.

Methods

In this study, a deep survival learning model (DSLM) for stage III NSCLC was developed based on the Surveillance, Epidemiology, and End Results (SEER) database and was independently tested with another external cohort from our institute. DSLM was

SUBMITTER: Yang L 

PROVIDER: S-EPMC9678103 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature