Peer-Reviewed Publication
J Clin Med2025;14(15)August 3, 2025Journal Article

A Novel Deep Learning Model for Predicting Colorectal Anastomotic Leakage: A Pioneer Multicenter Transatlantic Study.

Miguel Mascarenhas1,2,3,4,5, Francisco Mendes1,2,3,5, Filipa Fonseca6, Eduardo Carvalho7,8, Andre Santos3,5, Daniela Cavadas6, Guilherme Barbosa7,8, Antonio Pinto da Costa5,9, Miguel Martins1,2,3, Abdullah Bunaiyan10, Maísa Vasconcelos11, Marley Ribeiro Feitosa11, Shay Willoughby10, Shakil Ahmed10, Muhammad Ahsan Javed10, Nilza Ramião7,8, Guilherme Macedo1,2,3, Manuel Limbert6
1Precision Medicine Unit, Department of Gastroenterology, Unidade Local de Saúde São João, 4200-319 Porto, Portugal.
2WGO Gastroenterology and Hepatology Training Center, 4200-427 Porto, Portugal.
3Faculty of Medicine, University of Porto, 4200-427 Porto, Portugal.
4CINTESIS-RISE, Department of Community Medicine, Information and Health Decision Sciences (MEDCIDS), Faculty of Medicine, University of Porto, 4200-427 Porto, Portugal.
5DigestAID, Digestive Artificial Intelligence Development, 4200-135 Porto, Portugal.
6Instituto Português de Oncologia de Lisboa, 1099-023 Lisboa, Portugal.
7INEGI-Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial, 4200-465 Porto, Portugal.
8Faculty of Engineering, University of Porto, 4200-427 Porto, Portugal.
9Hospital Universitario Puerta de Hierro Majadahonda, 28222 Madrid, Spain.
10Royal Liverpool University Hospital, Liverpool L7 8YE, UK.
11Hospital das Clinicas da Faculdade de Medicina da Universidade de São Paulo, Clínica de Ribeirao Preto, Ribeirao 05403-010, Brazil.

Abstract

Background/Objectives: Colorectal anastomotic leak (CAL) is one of the most severe postoperative complications in colorectal surgery, impacting patient morbidity and mortality. Current risk assessment methods rely on clinical and intraoperative factors, but no real-time predictive tool exists. This study aimed to develop an artificial intelligence model based on intraoperative laparoscopic recordi…

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