Clinical Trial: Explainable Machine Learning for Predicting Early Gastric Cancer

U.S., July 3 -- ClinicalTrials.gov registry received information related to the study (NCT07047937) titled 'Explainable Machine Learning for Predicting Early Gastric Cancer' on June 04.

Brief Summary: Abstract Background: Early detection of gastric cancer is crucial for improving patient survival rates. Currently, the primary method for diagnosing early-stage gastric cancer is endoscopy, which has various limitations. Additionally, single laboratory tests continue to fall short of the requirements for early screening. This study aims to develop a machine learning (ML) model using clinical data to predict early-stage gastric cancer and apply SHapley Additive exPlanation (SHAP) values to explain the ML model.

Methods: This study involved pa...