Predicting Metastasis In Gastric Cancer Patients: Machine Learning-based Approaches

This study aimed to predict the metastasis status of gastric cancer (GC) patients using machine learning (ML) based models, including decision tree, random forest, Naive Bayes, Support Vector Machine, Neural Network and Logistic Regression. The performance of the models was evaluated using precision, F1 score, sensitivity, specificity, area under the curve of receiver operating characteristic curve and precision-recall AUC. The study included 733 patients diagnosed with GC at Taleghani tertiary Hospital, and the inclusion criteria were definitive pathological diagnosis of primary gastric adenocarcinoma and tumor metastasis from 2014 to 2019.