Solving data quality issues of fundus images in real-world settings by ophthalmic AI.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 36812885.
- Also identified by DOI 10.1016/j.xcrm.2023.100951 and PMC identifier 9975325.
- Licence recorded as CC BY-NC-ND.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
Liu et al.<sup>1</sup> develop a deep-learning-based flow cytometry-like image quality classifier, DeepFundus, for the automated, high-throughput, and multidimensional classification of fundus image quality. DeepFundus significantly improves the real-world performance of established artificial intelligence diagnostics in detecting multiple retinopathies.
Medical subject headings
- Artificial Intelligence
- Data Accuracy