Table 1 Summary of the major publications in retinal analysis using DL, grouped by standard multiple-field fundus photography, ultra-wide field photography and smartphone-based photography
Authors and year of publication | Approach | Training dataset | Validation datasets | Performance |
|---|---|---|---|---|
Standard view photography | ||||
 Gulshan et al. 2016 [35] | Inception-V3 network | Public EyePACS and Messidor-2 (> 120,000 images) | Public EyePACS-1 and Messidor-2 (> 10,000 images) | EyePACS-1 |
AUC: 0.99 | ||||
Sensitivity: 90% | ||||
Specificity: 98% | ||||
Messidor-2 | ||||
AUC: 0.99 | ||||
Sensitivity: 87% | ||||
Specificity: 99% | ||||
 Abrà moff et al. 2016 [46] | AlexNet/VGG network | Public Messidor-2 | Public Messidor-2 (~ 2000 images) | AUC: 0.98 |
Sensitivity: 97% | ||||
Specificity: 87% | ||||
 Ting et al. 2017 [26] | VGGNet-19 network | Proprietary SiDRP 2010–2013 (> 76,000 images) | Proprietary SiDRP 14–15 and 10 others (> 112,000 images) | SiDRP 2014–2015 |
AUC: 0.93 | ||||
Sensitivity: 91% | ||||
Specificity: 92% | ||||
Others | ||||
AUC range: 0.89 to 0.98 | ||||
Sensitivity range: 92 to 100% | ||||
Specificity: 76 to 92% | ||||
 Gargeya et al. 2017 [47] | Customised CNN network | Public EyePACS-1 (> 75,000 images) | Public EyePACS-1, Messidor-2,E-Ophtha (> 17,000 images) | EyePACS-1 |
AUC: 0.97 | ||||
Sensitivity: 94% | ||||
Specificity: 96% | ||||
Messidor-2 and E-Ophtha | ||||
AUC range: 0.83 to 0.95 | ||||
Sensitivity range: 74 to 93% | ||||
Specificity range: 87 to 94% | ||||
 Abrà moff et al. 2018 [34] | AlexNet/VGGNet network | Public Messidor-2 | Proprietary Primary care sites (~ 900 patients) | Sensitivity: 87% |
Specificity: 91% | ||||
 Keel et al. 2018 [48] | Inception-V3 network | Public LabelMe (~ 59,000) | Proprietary Endocrinology outpatient services (96 patients) | Sensitivity: 92% |
Specificity: 94% | ||||
 Kanagasingam et al. 2018 [49] | Inception-V3 network | Public and proprietary DiaRetDB1, EyePACS, Australian tele-eye care (30,000 images) | Proprietary Primary care (~ 200 patients) | Sensitivity: 92% |
 Gulshan et al. 2019 [50] | Inception-v4 network | Public EyePACS and Messidor-2 (> 144,000 images) | Proprietary Two eye hospitals (~ 6000 images) | AUC range: 0.97 to 0.98 |
Sensitivity range: 89 to 92% | ||||
Specificity range: 92 to 95% | ||||
 Raumviboonsuk et al. 2019 [51] | Inception-v4 network | Public EyePACS and Messidor-2 (> 120,000 images) | Proprietary Hospitals and health centers (~ 30,000 images) | AUC: 0.99 |
Sensitivity: 96.9% | ||||
Specificity: 95.3% | ||||
 Bellemo et al. 2019 [52] | VGGNet/ResNet network | Proprietary SiDRP 2010–2013 (> 76,000 images) | Proprietary Mobile screening unit (> 4000 images) | AUC: 0.97 |
Sensitivity: 92% | ||||
Specificity: 89% | ||||
Ultra-wide field photography | ||||
 Wang et al. 2018 [53] | EyeArt software | – | Proprietary Eye clinics (~ 1500 images) | AUC: 0.85 |
Sensitivity: 90% | ||||
Specificity: 54% | ||||
 Nagasawa at al. 2019 [54] | VGGNet-16 network | Proprietary Hospitals (< 400 images) | Proprietary Hospitals (< 400 images) | AUC: 0.97 |
Sensitivity: 95% | ||||
Specificity: 97% | ||||
Smartphone-based photography | ||||
 Rajalakshmi et al. 2018 [55] | EyeArt software | – | Proprietary Tertiary care diabetes hospital (~ 300 images) | Sensitivity: 96% |
Specificity: 80% | ||||
 Natarajan et al. 2019 [56] | Remidio software Inception-V3 network | Public and proprietary EyePACS and hospitals (> 52,000 images) | Proprietary Population-based screening (> 4000 images) | Sensitivity range: 96 to 100% |
Specificity range: 79 to 88% | ||||
 Rogers et al. 2019 [57] | Pegasus software | – | Public and proprietary IDRiD and research laboratory study (> 6000 images) | AUC range: 89 to 99% |
Sensitivity range: 82 to 93% | ||||
Specificity range: 82 to 94% | ||||