Getting the best out of artificial intelligence in endoscopy

Endoscopy 2025; 57(07): 717-718
DOI: 10.1055/a-2566-9576

Editorial

Referring to Jong MR et al. doi: 10.1055/a-2537-3510

Authors

Laurence B. Lovat

¹Division of Surgery and Interventional Science, University College London, London, United Kingdom of Great Britain and Northern Ireland

References
1 Hassan C, Spadaccini M, Mori Y. et al. Real-time computer-aided detection of colorectal neoplasia during colonoscopy: a systematic review and meta-analysis. Ann Intern Med 2023; 176: 1209-1220
2 Djinbachian R, Rex DK, von Renteln D. Optical polyp diagnosis in the era or artificial intelligence. Am J Gastroenterol 2024;
3 Visrodia K, Singh S, Krishnamoorthi R. et al. Magnitude of missed esophageal adenocarcinoma after Barrett’s esophagus diagnosis: a systematic review and meta-analysis. Gastroenterology 2016; 150: 599-e15
4 Messmann H, Bisschops R, Antonelli G. et al. Expected value of artificial intelligence in gastrointestinal endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement. Endoscopy 2022; 54: 1211-1231
5 Jong MR, Jaspers TJM, van Eijck van Heslinga RAH. et al. The development and ex vivo evaluation of a computer-aided quality control system for Barrett’s esophagus endoscopy. Endoscopy 2025; 57
6 Schölvinck DW, Van Der Meulen K, Bergman JJGHM. et al. Detection of lesions in dysplastic Barrett’s esophagus by community and expert endoscopists. Endoscopy 2017; 49: 113-120
7 Korteling JEH, Paradies GL, Sassen-van Meer JP. Cognitive bias and how to improve sustainable decision making. Front Psychol 2023; 14: 1129835
8 Davidson T, Denain J-S, Villalobos P. et al. AI capabilities can be significantly improved without expensive retraining. arXiv 2023;