Emerging Trends and Advances in the Diagnosis of Gastrointestinal Diseases

Abstract

Recently, Artificial Intelligence (AI)-based techniques, namely machine learning (ML) and deep learning (DL) have gained exceptional devotion in conducting the analysis of medical images because of their capacity to provide outstanding results that can compete with specialists. Despite the rise of artificial intelligence-based research on peptic ulcer diseases, limited reviews are available concerning this area. For this purpose, the researcher reviewed artificial intelligence techniques used for detecting and classifying gastrointestinal diseases in wireless capsule endoscopy images. Furthermore, this study investigates the tremendous potential for peptic ulcer disease that has been cited in the prior literature. The findings demonstrated the value of WCE picture analysis using machine learning and deep learning techniques. Additionally, further, limitations were found in the availability of datasets and assessment measures, which have an impact on the reproducibility of experiments.