原始数据集

In this study, machine learning algorithms94 was used instead of traditional statistical analysis methods to process the clinical95 characteristics data of patients with IDC, and a machine learning-based predictive96 model was developed to discover the relationship between certain independent97 variables and the likelihood of patients with IDC developing distant organ metastasis.98 Focusing on the predictive models of four algorithms: Logistic Regression, SVM,99 Random Forest and XGBoost, and using them as base models for integration to100 construct hybrid models. A ten-fold cross-validation was used to compare the101 accuracy, recall, precision, and AUC value of each model to predict the risk of cancer102 metastasis in patients with IDC, thereby assisting clinicians in making more rational103 clinical decisions and enabling patients to receive treatment earlier.