Real-Life Clinical Validation of AI-Assisted Detection and Differentiation of Pleomorphic Lesions in Capsule Endoscopy

This was the first multicentric study proving AI-assisted CapE reading superiority compared with conventional reading. The inclusion of videos from multiple devices addresses the interoperability challenge, whereas including patients from 4 countries and 2 different continents assures a diverse demographic context. AI achieved gastroenterologist-level identification of small-bowel lesions, surpassing conventional reading methods in both lesion detection and characterization.

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Publication Details

Journal
The American Journal of Gastroenterology
Published
2025-08-28
DOI
https://doi.org/10.14309/ajg.0000000000003756
Citations
1
Primary Topic
Gastrointestinal Bleeding Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
1.81
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article

Real-Life Clinical Validation of AI-Assisted Detection and Differentiation of Pleomorphic Lesions in Capsule Endoscopy

João Ferreira, Marcos Eduardo Lera dos Santos, Cecílio Santander, Maria João Almeida et al.
1 citations
The American Journal of Gastroenterology
Gastrointestinal Bleeding Diagnosis and Treatment
1.81
article

Real-Life Clinical Validation of AI-Assisted Detection and Differentiation of Pleomorphic Lesions in Capsule Endoscopy

João Ferreira, Marcos Eduardo Lera dos Santos, Cecílio Santander, Maria João Almeida, Miguel Martins, Pedro Emartino Bezerra Campelo, Pedro Cardoso, Tiago Cúrdia Gonçalves, Hélder Cardoso, Patrícia Andrade, Miguel Mascarenhas, José Cotter, António Miguel Martins Pinto da Costa, William Sonnier, Francisco Mendes, J. A. Palma, C Macedo, Guilherme Macedo, Thiago Alves Cavalcante, Bruno Rosa, Joana Mota, Jorge Mendoza, João Afonso, Tiago Ribeiro, Matheus Ferreira de Carvalho, Eduardo Horneaux de Moura, Erika Borges Fortes, Ana Pérez-Gonzalez
article en
1 citations

Abstract

This was the first multicentric study proving AI-assisted CapE reading superiority compared with conventional reading. The inclusion of videos from multiple devices addresses the interoperability challenge, whereas including patients from 4 countries and 2 different continents assures a diverse demographic context. AI achieved gastroenterologist-level identification of small-bowel lesions, surpassing conventional reading methods in both lesion detection and characterization.

The American Journal of Gastroenterology
University of Alabama (US), Universidade do Porto (PT), Hospital Israelita Albert Einstein (BR), Hospital de São João (PT), Hospital da Senhora da Oliveira Guimarães (PT), Hospital Universitario Puerta de Hierro Majadahonda (ES), Hospital Universitario de La Princesa (ES), Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (BR), Hospital Sírio-Libanês (BR), Hospital São Paulo (BR), Artificial Intelligence in Medicine (Canada) (CA), University of South Alabama (US), University of Minho (PT)
Openalex Percentile: Top 13%
Gastrointestinal Bleeding Diagnosis and Treatment
1.81
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