A Comprehensive Review of Artificial Intelligence and Colon Capsule Endoscopy: Opportunities and Challenges
Joana Mota, Maria João Almeida, Francisco Mendes, Miguel Martins, Tiago Ribeiro, João Afonso, Pedro Cardoso, Hélder Cardoso, Patrícia Andrade, João Canas Ferreira, Guilherme Macedo, Miguel Mascarenhas
Abstract
Colon capsule endoscopy (CCE) enables a comprehensive, non-invasive, and painless evaluation of the colon, although it still has limited indications. The lengthy reading times hinder its wider implementation, a drawback that could potentially be overcome through the integration of artificial intelligence (AI) models. Studies employing AI, particularly convolutional neural networks (CNNs), demonstrate great promise in using CCE as a viable option for detecting certain diseases and alterations in the colon, compared to other methods like colonoscopy. Additionally, employing AI models in CCE could pave the way for a minimally invasive panenteric or even panendoscopic solution. This review aims to provide a comprehensive summary of the current state-of-the-art of AI in CCE while also addressing the challenges, both technical and ethical, associated with broadening indications for AI-powered CCE. Additionally, it also gives a brief reflection of the potential environmental advantages of using this method compared to alternative ones.