Real-World Assessment of the Efficacy of Computer-Assisted Diagnosis in Colonoscopy: A Single Institution Cohort Study in Singapore
Computer-Assisted Diagnosis is therefore a promising adjunct in colonoscopy with substantial clinical implications. Accurate identification of low-risk non-adenomatous polyps encourages the adoption of "resect-and-discard" strategies. However, further calibration of AI systems is needed before the acceptance of such strategies as the new standard of care.
Authors
- Baldwin Po Man Yeung (ORCID: https://orcid.org/0000-0002-0656-2181)
- Cesare Hassan (ORCID: https://orcid.org/0000-0001-7167-1459)
- Fung Joon Foo (ORCID: https://orcid.org/0000-0003-0461-7510)
- Frederick H. Koh (ORCID: https://orcid.org/0000-0002-3717-4480)
- Fang-Ting Wan
- Clarence Kwan
- Shuen-Ern Chin
- Ronja Maria Birgitta Lagström (ORCID: https://orcid.org/0000-0002-6726-7573)
- Juinn Huar Kam (ORCID: https://orcid.org/0000-0002-2478-9689)
- Ismail Gögenür (ORCID: https://orcid.org/0000-0002-3753-268X)
- Gabrielle Eloise Ming Yen Koh
- Brittany Ng
Institutions
- Humanitas University (IT)
- National University of Singapore (SG)
- Nanyang Technological University (SG)
- Istituti di Ricovero e Cura a Carattere Scientifico (IT)
- Zealand University Hospital Køge (DK)
- Sengkang General Hospital (SG)
Publication Details
- Journal
- Mayo Clinic Proceedings Digital Health
- Published
- 2024-10-28
- DOI
- https://doi.org/10.1016/j.mcpdig.2024.10.002
- Citations
- 1
- Primary Topic
- Colorectal Cancer Screening and Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.28
Funders
- Medtronic
- Medtronic