Artificial intelligence applications in ophthalmic optical coherence tomography: a 12-year bibliometric analysis
The annual number of articles on AI applications in ophthalmic OCT has grown rapidly. The United States holds a prominent position. Institutions like the University of California System and the University of London are spearheading advancements. Initial researches centered on the automatic recognition and diagnosis of ocular diseases leveraging traditional machine learning (ML) technology and OCT images. Nowadays, the imaging process algorithm selection has shifted its focus towards DL. Concurrently, optical coherence tomography angiography (OCTA) and computer-aided diagnosis (CAD) have emerged as key areas of contemporary research.
Authors
- Ruoyu Wang (ORCID: https://orcid.org/0000-0002-3644-1284)
- Weihua Yang (ORCID: https://orcid.org/0000-0002-7629-0193)
- Li Sun (ORCID: https://orcid.org/0000-0002-4421-7207)
- Xinya Hu (ORCID: https://orcid.org/0009-0007-4582-6323)
- Shaochong Zhang (ORCID: https://orcid.org/0000-0002-2212-7139)
Institutions
- Nanjing University of Chinese Medicine (CN)
- Jinan University (CN)
- Karolinska Institutet (SE)
- First Affiliated Hospital of Guangzhou Medical University (CN)
- Jiangsu Provincial Academy of Traditional Chinese Medicine (CN)
- Guangzhou Medical University (CN)
Publication Details
- Journal
- International Journal of Ophthalmology
- Published
- 2024-11-19
- DOI
- https://doi.org/10.18240/ijo.2024.12.19
- Citations
- 6
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 2.43
Funders
- Government of Jiangsu Province