Artificial Intelligence-based Diagnostic Analysis for Wireless Capsule Endoscopy in Obscure Bowel Disease Detection: A Potential

Abstract

Wireless Capsule Endoscopy (WCE) has become one of the most practiced techniques in gastrointestinal (GI) tract disease detection. WCE is expecting to benefit more if examinations are carried out with more advanced AI technologies. Research development in the area of artificial intelligence (AI) for gastrointestinal endoscopy has increased widely to detect multiple lesions, bleeding areas, cancer with more accuracy and detecting the severity of the abnormal area. In this study, we have in view to summarize the importance of AI in Capsule Endoscopy bowel disease detection. Reading capsule endoscopy images and watching its videos is a very time-consuming and error-prone process, AI computerized algorithms if embedded with the device will surely help in detecting every minor problem efficiently. Through this work, we are trying to suggest how useful is AI- based predictive algorithms for WCE in detecting automatic abnormal region classification. A number of studies have shown that an AI-driven method has great potential for investigating various fields of the healthcare sector. This paper gives an outline of the existing position and future potential of AI in Wireless Capsule endoscopy.