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Editorial
. 2019 Sep;33(9):1357-1358.
doi: 10.1038/s41433-019-0535-7. Epub 2019 Jul 29.

Introducing automated diabetic retinopathy systems: it's not just about sensitivity and specificity

Caroline Jane Styles  1
Affiliations
Editorial

Introducing automated diabetic retinopathy systems: it's not just about sensitivity and specificity

Caroline Jane Styles. Eye (Lond). 2019 Sep.
No abstract available

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Conflict of interest statement

The author declares that she has no conflict of interest.

References

    1. Gulshan V, Rajan R, Widner K, Wu D, Wubbels P, Rhodes T, et al. Performance of a deep learning alogorithm vs manual grading for detecting diabetic retinopathy in India. JAMA Ophthalmology. 2019. 10.1001/jamaophthalmol.2019.2004. Published online 13 Jun 2019. - PMC - PubMed
    1. Philip S, Fleming A, Goatman K, Fonseca S, McNamee P, Scotland G, et al. The efficacy of automated “disease/no disease” grading for diabetic retinopathy in a systematic screening programme. BJO. 2007;91:1512–7. doi: 10.1136/bjo.2007.119453. - DOI - PMC - PubMed
    1. Fleming A, Goatman K, Philip S, Prescott G, Sharp P, Olson J. Automated grading for diabetic retinopathy: a large-scale audit using arbitration by clinical experts. BJO. 2010;94:1606–10. doi: 10.1136/bjo.2009.176784. - DOI - PubMed

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