Artificial intelligence and capsule endoscopy: unravelling the future

Miguel Mascarenhas; João Afonso; Patrícia Andrade; Hélder Cardoso; Guilherme Macedo

Authors Miguel Mascarenhas, João Afonso, Patrícia Andrade, Hélder Cardoso, Guilherme Macedo.

Abstract

The applicability of artificial intelligence (AI) in gastroenterology is a hot topic because of its disruptive nature. Capsule endoscopy plays an important role in several areas of digestive pathology, namely in the investigation of obscure hemorrhagic lesions and the management of inflammatory bowel disease. Therefore, there is growing interest in the use of AI in capsule endoscopy. Several studies have demonstrated the enormous potential of using convolutional neural networks in various areas of capsule endoscopy. The exponential development of the usefulness of AI in capsule endoscopy requires consideration of its medium- and long-term
impact on clinical practice. Indeed, the advent of deep learning in the field of capsule endoscopy, with its evolutionary character, could lead to a paradigm shift in clinical activity in this setting. In this review, we aim to illustrate the state of the art of AI in the field of capsule endoscopy.

Keywords Capsule endoscopy, artificial intelligence, deep learning, machine learning, gastroenterology

Ann Gastroenterol 2021; 34 (3): 300-309