Use of radiomics to extract splenic features to predict prognosis of patients with gastric cancer

Radiomics allows for mining of imaging data to examine tissue characteristics non-invasively, which can be used to predict the prognosis of a patient. This study explored the use of imaging techniques to evaluate splenic tissue characteristics to predict the prognosis of patients with gastric cancer. Computed tomography images from patients with gastric cancer were collected retrospectively. Splenic image characteristics, extracted with pyradiomics, of patients in the training group were randomly divided. Characteristics with a P value