Deep Learning Model for Predicting Gastric Cancer Recurrence

Using CT imaging data, a deep learning model accurately predicts postoperative recurrence in gastric cancer patients. Developed and validated on 2,813 patients, the model showed excellent performance in identifying high-risk cases of recurrence. The deep learning fusion signature outperformed clinical models and baseline deep learning signatures, demonstrating its potential as a prognostic factor for patients undergoing radical surgery for gastric cancer.