Impact of Introducing Artificial Intelligence on Colonoscopy: A Retrospective Study on Potential Benefits and Drawbacks
The introduction of CAD-assisted colonoscopy significantly improved ADR and PDR. However, CAD reliance may lead to lapses in attention toward independent lesion detection by endoscopists. It is essential to consider how CAD should be utilized in clinical practice to maximize its benefits.
Authors
- Takuji Gotoda (ORCID: https://orcid.org/0000-0001-6904-6777)
- Yuki Yamada (ORCID: https://orcid.org/0000-0003-2113-5329)
- Masako Nakayama
- Yoshimasa Mıura (ORCID: https://orcid.org/0000-0002-7464-7283)
- Robert Bechara (ORCID: https://orcid.org/0000-0002-4543-5580)
- Zhehao Dai (ORCID: https://orcid.org/0000-0002-0363-7563)
- Hirofumi Kogure (ORCID: https://orcid.org/0000-0002-2355-7309)
- Ayaka Takasu (ORCID: https://orcid.org/0000-0003-0130-7170)
Institutions
- Nihon University (JP)
- Queen's University (CA)
- Japanese Foundation For Cancer Research (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- Journal of Gastroenterology and Hepatology
- Published
- 2025-07-01
- DOI
- https://doi.org/10.1111/jgh.17040
- Citations
- 5
- Primary Topic
- Colorectal Cancer Screening and Detection
- Type
- article
- Field-Weighted Citation Impact
- 5.23