Artificial intelligence (AI) research in endoscopy is being translated at rapid pace with a number of approved devices now available for use in luminal endoscopy. However, the published literature for AI in biliopancreatic endoscopy is predominantly limited to early pre-clinical studies including applications for diagnostic EUS and patient risk stratification. Potential future use cases are highlighted in this manuscript including optical characterisation of strictures during cholangioscopy, prediction of post-ERCP acute pancreatitis and selective biliary duct cannulation difficulty, automated report generation and novel AI-based quality key performance metrics. To realise the full potential of AI and accelerate innovation, it is crucial that robust inter-disciplinary collaborations are formed between biliopancreatic endoscopists and AI researchers.

Artificial intelligence, Endoscopic retrograde cholangiopancreatography, Endoscopic ultrasonography, Machine learning
dx.doi.org/10.1016/j.bpg.2020.101724, hdl.handle.net/1765/133331
Best Practice and Research in Clinical Gastroenterology
Erasmus MC: University Medical Center Rotterdam

Ahmad, O.F. (Omer F.), Stassen, P. (Pauline), & Webster, G.J. (George J.). (2020). Artificial intelligence in biliopancreatic endoscopy: Is there any role?. Best Practice and Research in Clinical Gastroenterology. doi:10.1016/j.bpg.2020.101724