Large-scale observational study of AI-based patient and surgical material verification system in ophthalmology: real-world evaluation in 37 529 cases
The AI-based surgical safety system significantly increased near miss detection and showed potential economic benefits. However, errors in non-authenticated cases underscore the importance of consistent system use and integration with existing safety protocols. These findings emphasise that while AI can enhance surgical safety, its effectiveness depends on proper implementation and continuous refinement.
Authors
- Naofumi Ishitobi
- Masahiro Akada (ORCID: https://orcid.org/0009-0005-4603-7444)
- Hayato Tanaka
- Hitoshi Tabuchi (ORCID: https://orcid.org/0000-0002-9098-0430)
- Hodaka Deguchi
- Mao Tanabe
- Yuta Nakaniida
Institutions
- Hiroshima University (JP)
Publication Details
- Journal
- BMJ Quality & Safety
- Published
- 2024-11-29
- DOI
- https://doi.org/10.1136/bmjqs-2024-018018
- Citations
- 3
- Primary Topic
- Intraocular Surgery and Lenses
- Type
- article
- Field-Weighted Citation Impact
- 1.62
Funders
- Japan Agency for Medical Research and Development