AI-Assisted Cholangioscopy Trial Opens: Real-Time CNN Model for Biliary Stricture Diagnosis — What Gastroenterologists Need to Know

References

1. 1.Mayo Clinic. (2024). Real-Time Cholangioscopy Artificial Intelligence Evaluation of Biliary Strictures. ClinicalTrials.gov. NCT05779436. https://clinicaltrials.gov/study/NCT05779436
2. 2.Saraiva, M. M., Ferreira, J. P., & Ribeiro, T. (2022). Artificial intelligence and cholangioscopy - A systematic review. World Journal of Gastrointestinal Endoscopy, 14(7), 356-365. https://doi.org/10.4253/wjge.v14.i7.356
3. 3.Robles-Medranda, C., Oleas, R., & Nebel, J. A. (2021). Artificial intelligence in digestive endoscopy - Where are we and where are we going? World Journal of Gastroenterology, 27(21), 2681-2703. https://doi.org/10.3748/wjg.v27.i21.2681
4. 4.Korrapati, P., Ciolino, J. D., & Wani, S. (2020). The efficacy of peroral cholangioscopy for difficult biliary stones and indeterminate strictures: a systematic review and meta-analysis. Endoscopy International Open, 8(8), E1173-E1183. https://doi.org/10.1055/a-1072-4258
5. 5.Navaneethan, U., Njei, B., & Lourdusamy, V. (2015). Comparative effectiveness of biliary brush cytology and intraductal biopsy for detection of malignant biliary strictures: a systematic review and meta-analysis. Gastrointestinal Endoscopy, 81(1), 168-176. https://doi.org/10.1016/j.gie.2015.06.017
6. 6.Pereira, P., Vilas-Boas, F., & Peixoto, A. (2023). Artificial intelligence in cholangioscopy: A new era for biliary endoscopy. World Journal of Methodology, 13(4), 234-245. https://doi.org/10.5662/wjm.v13.i4.234