A Comprehensive Review of Artificial Intelligence and Colon Capsule Endoscopy: Opportunities and Challenges

• Type: Another Publication in an International Scientific Journal
• Date: 2024

Authors

Mota, J (Author) Other; Almeida, MJ (Author) Other; Mendes, F (Author) Other; Martins, M (Author) Other; Ribeiro, T (Author) Other; Afonso, J (Author) Other; Cardoso, P (Author) Other; Cardoso, H (Author) Other; Andrade, P (Author) Other; Ferreira, J (Author) Other; Macedo G (Author) FMUP; Mascarenhas, M (Author) Other

Journal

Title: Diagnostics

Vol. 14

Final page: 2072

Publisher: MDPI

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-017-4HN

DOI: 10.3390/diagnostics14182072

Abstract (EN): 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12