Abstract
Objectives
The purpose of this study is to assess the accuracy of artificial intelligence (AI)-based screening for diabetic retinopathy (DR) and to explore the feasibility of applying AI-based technique to community hospital for DR screening.
Methods
Nonmydriatic fundus photos were taken for 889 diabetic patients who were screened in community hospital clinic. According to DR international classification standards, ophthalmologists and AI identified and classified these fundus photos. The sensitivity and specificity of AI automatic grading were evaluated according to ophthalmologists’ grading.
Results
DR was detected by ophthalmologists in 143 (16.1%) participants and by AI in 145 (16.3%) participants. Among them, there were 101 (11.4%) participants diagnosed with referable diabetic retinopathy (RDR) by ophthalmologists and 103 (11.6%) by AI. The sensitivity, specificity and area under the curve (AUC) of AI for detecting DR were 90.79% (95% CI 86.4–94.1), 98.5% (95% CI 97.8–99.0) and 0.946 (95% CI 0.935–0.956), respectively. For detecting RDR, the sensitivity, specificity and AUC of AI were 91.18% (95% CI 86.4–94.7), 98.79% (95% CI 98.1–99.3) and 0.950 (95% CI 0.939–0.960), respectively.
Conclusion
AI has high sensitivity and specificity in detecting DR and RDR, so it is feasible to carry out AI-based DR screening in outpatient clinic of community hospital.
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Funding
This work was supported by Advanced and Appropriate Technology Promotion Project of Shanghai Health Commission (2019SY012), Project of Shanghai Municipal Commission of Health and Family Planning (201740001, 20164Y0180), Science and technology innovation action plan of Shanghai Science and Technology Commission (17411952900), Project of Shanghai Jing’an District Health Research (2016QN06, 2019QN07), Project of Shanghai Jing’an District Municipal Commission of Health and Family Planning (2018MS12, 2016084). Project of Shanghai Shibei Hospital of Jing’an District (2018SBMS10).
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He, J., Cao, T., Xu, F. et al. Artificial intelligence-based screening for diabetic retinopathy at community hospital. Eye 34, 572–576 (2020). https://doi.org/10.1038/s41433-019-0562-4
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DOI: https://doi.org/10.1038/s41433-019-0562-4
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