Determining the prognosis of Lung cancer from mutated genes using a deep learning survival model: a large multi-center study.

ABSTRACT:

Background

Gene status has become the focus of prognosis prediction. Furthermore, deep learning has frequently been implemented in medical imaging to diagnose, prognosticate, and evaluate treatment responses in patients with cancer. However, few deep learning survival (DLS) models based on mutational genes that are directly associated with patient prognosis in terms of progression-free survival (PFS) or overall survival (OS) have been reported. Additionally, DLS models have not been applied to determine IO-related prognosis based on mutational genes. Herein, we developed a deep learning method to predict the prognosis of patients with lung cancer treated with or without immunotherapy (IO).

Methods

Samples from 6542 patients from different centers were subjected to genome seq

SUBMITTER: Peng J 

PROVIDER: S-EPMC10625246 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature