Predicting postoperative gastric cancer prognosis based on inflammatory factors and machine learning technology.

ABSTRACT:

Objective

There is a strong association between gastric cancer and inflammatory factors. Many studies have shown that machine learning can predict cancer patients' prognosis. However, there has been no study on predicting gastric cancer death based on machine learning using related inflammatory factor variables.

Methods

Six machine learning algorithms are applied to predict total gastric cancer death after surgery.

Results

The Gradient Boosting Machine (GBM) algorithm factors accounting for the prognosis weight outcome show that the three most important factors are neutrophil-lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR) and age. The total postoperative death model showed that among patients with gastric cancer from the predictive test group: The highest acc

SUBMITTER: Zhou CM 

PROVIDER: S-EPMC10067164 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature