Influence of artificial intelligence on ophthalmologists’ judgments in glaucoma
In fundus photography-based glaucoma detection, the results of AI systems can influence physicians' judgments, particularly those of physicians with less experience.
Authors
- Toru Nakazawa (ORCID: https://orcid.org/0000-0002-5591-4155)
- Kenji Kashiwagi (ORCID: https://orcid.org/0000-0001-8506-8503)
- Masaki Tanito (ORCID: https://orcid.org/0000-0001-6512-7203)
- Xiaoyang Mao (ORCID: https://orcid.org/0000-0001-9531-3197)
- Takeshi Yoshitomi (ORCID: https://orcid.org/0000-0001-6529-4650)
- Masahiro Toyoura (ORCID: https://orcid.org/0000-0002-5897-7573)
- Atsuya Miki (ORCID: https://orcid.org/0000-0002-5618-7287)
- Kazuhiko Mori (ORCID: https://orcid.org/0000-0002-5505-4917)
- Kazuhide Kawase
Institutions
- Aichi Medical University (JP)
- Shimane University (JP)
- Tohoku University (JP)
- Fukuoka International University (JP)
- Kyoto Prefectural University of Medicine (JP)
- Nagoya University (JP)
- University of Yamanashi (JP)
- International University of Health and Welfare (JP)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-04-16
- DOI
- https://doi.org/10.1371/journal.pone.0321368
- Citations
- 2
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 2.72