Gastric diffuse-type adenocarcinoma represents a disproportionately high percentage of
cases of gastric cancers occurring in the young, and its relative incidence seems to be on …

Objectives Detecting early gastric cancer is difficult, and it may even be overlooked by
experienced endoscopists. Recently, artificial intelligence based on deep learning through …

Preoperative prediction of lymph node (LN) metastasis based on computed tomography
(CT) scans is an important task in gastric cancer, but few machine learning-based …

Background and objective Gastric cancer is a kind of tumor with high morbidity and mortality,
which seriously threatens people's health and life. It is of great significance to study the early …

Background and Aims This study aimed to evaluate the accuracy and effectiveness of the
convolutional neural network (CNN) in diagnosing gastric cancer and predicting the …

Gastric cancer is a significant contributor to cancer-related fatalities globally. The automated
segmentation of gastric tumors has the potential to analyze the medical condition of patients …

Gastric cancer (GC) is one of the deadliest malignancies in the world. Currently, clinical
treatment decisions are mostly made based on the extent of the tumor and its anatomy, such …

Abnormalities of the gastrointestinal tract are widespread worldwide today. Generally, an
effective way to diagnose these life-threatening diseases is based on endoscopy, which …

Previous studies on deep learning (DL) applications in pathology have focused on
pathologist-versus-algorithm comparisons. However, DL will not replace the breadth and …

Background and Aims The prognosis of esophageal cancer is relatively poor. Patients are
usually diagnosed at an advanced stage when it is often too late for effective treatment …