TY  - JOUR
N2  - 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.
AV  - public
JF  - Best Practice & Research Clinical Gastroenterology
UR  - https://doi.org/10.1016/j.bpg.2020.101724
VL  - 52-53
A1  - Ahmad, OF
A1  - Stassen, P
A1  - Webster, GJ
KW  - Artificial intelligence; Machine learning; Endoscopic retrograde cholangiopancreatography; Endoscopic ultrasonography
ID  - discovery10120844
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
SN  - 1532-1916
Y1  - 2021/06//
TI  - Artificial intelligence in biliopancreatic endoscopy: Is there any role?
ER  -