Abstract
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.
| Original language | English |
|---|---|
| Article number | 101724 |
| Journal | Best Practice and Research: Clinical Gastroenterology |
| Volume | 52-53 |
| DOIs | |
| Publication status | Published - Jun 2021 |
Bibliographical note
Publisher Copyright:© 2020 Elsevier Ltd
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