Table 2.
Summary of the weighted accuracy and precision of artificial intelligence software in predicting diabetic retinopathy and referable diabetic retinopathy
Author (year) | Any diabetic retinopathy | Referable diabetic retinopathy | ||||
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Weight | Accuracy (%) | Precision (%) | Weight | Accuracy (%) | Precision (%) | |
Nataranjan et al., (2019) | 0.044 | 91.12 | 60.53 | 0.035 | 89.25 | 39.47 |
Rajalakshmi et al., (2018) | 0.351 | 90.54 | 90.15 | 0.329 | 83.45 | 78.24 |
Sosale (a), (2020) | 0.403 | 92.11 | 87.87 | 0.437 | 92.67 | 74.60 |
Sosale (b), (2020) | 0.202 | 91.92 | 92.92 | 0.199 | 90.24 | 75.22 |
Weighted (%) | 91.48 | 88.48 | Weighted (%) | 89.03 | 75.09 |