Diagnosis of gastric cancer in role of endoscopic imaging techniques in artificial intelligence and machine learning applications: An overview

Abstract

Gastric cancer is a serious medical issue because its occurrence and death rates are increasing all over the world. Furthermore, obesity, tobacco use, alcohol consumption, and a few dietary defense elements are known cancer-causing agents. In some nations, early detection strategies have been shown to reduce GC-related morbidity and mortality. It offers therapies that are minimally invasive like most effective procedure is endoscopic resection. The most appropriate standard for using a procedure that is typically secure to precisely evaluate the lesions region. It is simple method and it can be expected difficult techniques can be viewed as in early stage of tumour in accurate diagnosis. A few uses of computerized method have arisen in the field of gastric malignant growth. For example, image diagnosis-based prediction conclusion and guess expectation, because of its viable computational power and learning capabilities. As a result, a detailed outline of how artificial intelligence can be used to treat gastric cancer through image-based endoscopic diagnosis and machine learning analysis applications this review, which demonstrates the future developments in this field for the early prediction of gastric cancer, it was also thoroughly discussed the possibility of AI models being over fitted, their accuracy, and their usefulness to clinical research in this field of image processing. In addition, in this review article was been detailed about synopsis of the therapy choices of malignant growth.