Peer-Reviewed Publication
Cancers (Basel)2024;16(10)May 17, 2024Journal Article
Deep Learning and High-Resolution Anoscopy: Development of an Interoperable Algorithm for the Detection and Differentiation of Anal Squamous Cell Carcinoma Precursors-A Multicentric Study.
Miguel Mascarenhas Saraiva1,2,3, Lucas Spindler4, Thiago Manzione5, Tiago Ribeiro1,2,3, Nadia Fathallah4, Miguel Martins1,2, Pedro Cardoso1,2,3, Francisco Mendes1,2, Joana Fernandes6,7, João Ferreira6,7, Guilherme Macedo1,2,3, Sidney Nadal5, Vincent de Parades4
1Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, 4200-427 Porto, Portugal.
2WGO Gastroenterology and Hepatology Training Center, 4200-427 Porto, Portugal.
3Faculty of Medicine, University of Porto, Alameda Professor Hernâni Monteiro, 4200-427 Porto, Portugal.
4Department of Proctology, GH Paris Saint-Joseph, 185, Rue Raymond Losserand, 75014 Paris, France.
5Department of Surgery, Instituto de Infectologia Emílio Ribas, São Paulo 01246-900, Brazil.
6Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal.
7DigestAID-Artificial Intelligence Development, Rua Alfredo Allen, 4200-135 Porto, Portugal.
Abstract
High-resolution anoscopy (HRA) plays a central role in the detection and treatment of precursors of anal squamous cell carcinoma (ASCC). Artificial intelligence (AI) algorithms have shown high levels of efficiency in detecting and differentiating HSIL from low-grade squamous intraepithelial lesions (LSIL) in HRA images. Our aim was to develop a deep learning system for the automatic detection and…
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