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Dataset Information

Development and validation of machine learning models to predict survival of patients with resected stage-III NSCLC.


ABSTRACT:

Objective

To compare the performance of three machine learning algorithms with the tumor, node, and metastasis (TNM) staging system in survival prediction and validate the individual adjuvant treatment recommendations plan based on the optimal model.

Methods

In this study, we trained three machine learning madel and validated 3 machine learning survival models-deep learning neural network, random forest and cox proportional hazard model- using the data of patients with stage-al3 NSCLC patients who received resection surgery from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database from 2012 to 2017,the performance of survival predication from all machine learning models were assessed using a concordance index (c-index) and the averaged c-

SUBMITTER: Jin L 

PROVIDER: S-EPMC10040845 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature