Development and validation of a nomogram model for lung cancer based on radiomics artificial intelligence score and clinical blood test data.

ABSTRACT:

Background

Artificial intelligence (AI) discrimination models using single radioactive variables in recognition algorithms of lung nodules cannot predict lung cancer accurately. Hence, we developed a clinical model that combines AI with blood test variables to predict lung cancer.

Methods

Between 2018 and 2021, 584 individuals (358 patients with lung cancer and 226 individuals with lung nodules other than cancer as control) were enrolled prospectively. Machine learning algorithms including lasso regression and random forest (RF) were used to select variables from blood test data, Logistic regression analysis was used to reconfirm the features to build the nomogram model. The predictive performance was assessed by performing the receiver operating characteristic (ROC)

SUBMITTER: Hu W 

PROVIDER: S-EPMC10090418 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature