The identification of diseases is inseparable from artificial intelligence. As an important
branch of artificial intelligence, convolutional neural networks play an important role in the …

BACKGROUND: A timely diagnosis of early gastric cancer (EGC) can greatly reduce the
death rate of patients. However, the manual detection of EGC is a costly and low-accuracy …

Upper gastrointestinal endoscopy is widely performed to detect early gastric cancers. As an
automated detection method for early gastric cancer from endoscopic images, a method …

Endoscopy is widely applied in the examination of gastric cancer. However, extensive
knowledge and experience are required, owing to the need to examine the lesion while …

Diagnosis and evaluation of early gastric cancer (EGC) using endoscopic images is
significantly important; however, it has some limitations. In several studies, the application of …

Gastric cancer is characterized by the growth of cancerous cells within the lining of the
stomach. Traditionally, this condition has been challenging to diagnose. However, today …

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 …

To evaluate the Early Gastric Cancer (EGC) detection in humans one of the most common
diseases that act as neoplastic disease and second-largest fatal tumor-based disease …

Background Visual inspection, lesion detection, and differentiation between malignant and
benign features are key aspects of an endoscopist's role. The use of machine learning for …

In this paper, we develop a deep learning model using dense neural network (DenseNet) to
detect the gastric cancer in stomach region using computerised tomography (CT) imaging …