Journal
SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES
Volume 37, Issue 10, Pages 7395-7400Publisher
SPRINGER
DOI: 10.1007/s00464-023-10412-3
Keywords
Artificial intelligence; Polyp detection; Colonoscopy; Adenoma detection; Endoscopy; Implementation research
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There is a wide variation in endoscopists' knowledge and perceptions of artificial intelligence (AI). While most endoscopists are optimistic about AI's capabilities in administrative and clinical tasks, they are reserved about its ability to provide personalized and empathetic care. Acceptance of AI-aided colonoscopy systems is more related to endoscopists' experience with using the program rather than their general knowledge or perceptions of AI.
BackgroundRecent developments in artificial intelligence (AI) systems have enabled advancements in endoscopy. Deep learning systems, using convolutional neural networks, have allowed for real-time AI-aided detection of polyps with higher sensitivity than the average endoscopist. However, not all endoscopists welcome the advent of AI systems.MethodsWe conducted a survey on the knowledge of AI, perceptions of AI in medicine, and behaviours regarding use of AI-aided colonoscopy, in a single centre 2 months after the implementation of Medtronic's GI Genius in colonoscopy. We obtained a response rate of 66.7% (16/24) amongst consultant-grade endoscopists. Fisher's exact test was used to calculate the significance of correlations.ResultsKnowledge of AI varied widely amongst endoscopists. Most endoscopists were optimistic about AI's capabilities in performing objective administrative and clinical tasks, but reserved about AI providing personalised, empathetic care. 68.8% (n = 11) of endoscopists agreed or strongly agreed that GI Genius should be used as an adjunct in colonoscopy. In analysing the 31.3% (n = 5) of endoscopists who disagreed or were ambivalent about its use, there was no significant correlation with their knowledge or perceptions of AI, but a significant number did not enjoy using the programme (p-value = 0.0128) and did not think it improved the quality of colonoscopy (p-value = 0.033).ConclusionsAcceptance of AI-aided colonoscopy systems is more related to the endoscopist's experience with using the programme, rather than general knowledge or perceptions towards AI. Uptake of such systems will rely greatly on how the device is delivered to the end user.
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