Radiomics based on machine learning algorithms could predict prognosis and postoperative chemotherapy benefits of patients with gastric cancer: a retrospective cohort study.

ABSTRACT: Traditional clinical characteristics have certain limitations in evaluating cancer prognosis. The radiomics features provide information on tumor morphology, tissue texture, and hemodynamics, which can accurately reflect personalized predictions. This study investigated the clinical value of radiomics features on contrast-enhanced computed tomography (CT) images in predicting prognosis and postoperative chemotherapy benefits for patients with gastric cancer (GC). For this study, 171 GC patients who underwent radical gastrectomy and pathology confirmation of the malignancy at the First Affiliated Hospital of Wenzhou Medical University were retrospectively enrolled. The general information, pathological characteristics, and postoperative chemotherapy information were collected. Patients were

SUBMITTER: Xiang Y 

PROVIDER: S-EPMC10643584 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature