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ABSTRACT: Objective
Cuproptosis-related genes are closely related to lung adenocarcinoma (LUAD), which can be analyzed via the analysis of long noncoding RNA (lncRNA). To date, the clinical significance and function of cuproptosis-related lncRNAs are still not well elucidated. Further analysis of cuproptosis-related prognostic lncRNAs is of great significance for the treatment, diagnosis, and prognosis of LUAD.Methods
In this study, a multiple machine learning (ML)-based computational approach was proposed for the identification of the cuproptosis-related lncRNAs signature (CRlncSig) via comprehensive analysis of cuproptosis, lncRNAs, and clinical characteristics. The proposed approach integrated multiple ML algorithms (least absolute shrinkage and selection operator regression analy
SUBMITTER: Yang L
PROVIDER: S-EPMC10234775 | biostudies-literature | 2023 Jun
REPOSITORIES: biostudies-literature