Machine learning reveals CAT gene as a novel potential diagnostic and prognostic biomarker in non-small cell lung cancer.

ABSTRACT:

Background

Non-small cell lung cancer (NSCLC) represents one of the most prevalent forms of lung cancer, with a five-year survival rate of 21.7%. There is an urgent need to identify pertinent biomarkers to inform the diagnosis and prognosis of tumors, particularly those that can be applied to different age groups. Herein, we would apply machine learning methods to specifically analyze the issue of biomarker applicability across different age groups in NSCLC.

Methods

Studies have shown a higher incidence of NSCLC in people over 40 years of age, and due to the limitations of data set, studies of individuals under 40 years of age were not included in this study. To simulate the human aging model as closely as possible, we gathered corresponding non-small cell lung cancer (NSCLC

SUBMITTER: Tian Y 

PROVIDER: S-EPMC11655766 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature