scholarly journals Evaluation of a System for Automatic Detection of Diabetic Retinopathy From Color Fundus Photographs in a Large Population of Patients With Diabetes: Response to Olson et al.

Diabetes Care ◽  
2008 ◽  
Vol 31 (8) ◽  
pp. e64-e64 ◽  
Author(s):  
M. D. Abramoff ◽  
M. Niemeijer ◽  
M. S.A. Suttorp-Schulten ◽  
M. A. Viergever ◽  
S. R. Russell ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Large Population ◽  
Automatic Detection ◽  
Patients With Diabetes ◽  
Fundus Photographs

scholarly journals Evaluation of a System for Automatic Detection of Diabetic Retinopathy From Color Fundus Photographs in a Large Population of Patients With Diabetes

Diabetes Care ◽  
2007 ◽  
Vol 31 (2) ◽  
pp. 193-198 ◽  
Author(s):  
M. D. Abramoff ◽  
M. Niemeijer ◽  
M. S.A. Suttorp-Schulten ◽  
M. A. Viergever ◽  
S. R. Russell ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Large Population ◽  
Automatic Detection ◽  
Patients With Diabetes ◽  
Fundus Photographs

scholarly journals Automatic detection of diabetic retinopathy and its progression in sequential fundus images of patients with diabetes

2018 ◽  
Vol 97 (4) ◽  
pp. e667-e669
Author(s):  
Alexander Dietzel ◽  
Carolin Schanner ◽  
Aura Falck ◽  
Nina Hautala
Keyword(s):  
Diabetic Retinopathy ◽  
Automatic Detection ◽  
Fundus Images ◽  
Patients With Diabetes

scholarly journals Longitudinal Screening for Diabetic Retinopathy in a Nationwide Screening Program: Comparing Deep Learning and Human Graders

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Jirawut Limwattanayingyong ◽  
Variya Nganthavee ◽  
Kasem Seresirikachorn ◽  
Tassapol Singalavanija ◽  
Ngamphol Soonthornworasiri ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Deep Learning ◽  
Screening Program ◽  
False Negative ◽  
False Negative Rate ◽  
Lower Sensitivity ◽  
Patients With Diabetes ◽  
Fundus Photographs ◽  
New Onset

Objective. To evaluate diabetic retinopathy (DR) screening via deep learning (DL) and trained human graders (HG) in a longitudinal cohort, as case spectrum shifts based on treatment referral and new-onset DR. Methods. We randomly selected patients with diabetes screened twice, two years apart within a nationwide screening program. The reference standard was established via adjudication by retina specialists. Each patient’s color fundus photographs were graded, and a patient was considered as having sight-threatening DR (STDR) if the worse eye had severe nonproliferative DR, proliferative DR, or diabetic macular edema. We compared DR screening via two modalities: DL and HG. For each modality, we simulated treatment referral by excluding patients with detected STDR from the second screening using that modality. Results. There were 5,738 patients (12.3% STDR) in the first screening. DL and HG captured different numbers of STDR cases, and after simulated referral and excluding ungradable cases, 4,148 and 4,263 patients remained in the second screening, respectively. The STDR prevalence at the second screening was 5.1% and 6.8% for DL- and HG-based screening, respectively. Along with the prevalence decrease, the sensitivity for both modalities decreased from the first to the second screening (DL: from 95% to 90%, p = 0.008 ; HG: from 74% to 57%, p < 0.001 ). At both the first and second screenings, the rate of false negatives for the DL was a fifth that of HG (0.5-0.6% vs. 2.9-3.2%). Conclusion. On 2-year longitudinal follow-up of a DR screening cohort, STDR prevalence decreased for both DL- and HG-based screening. Follow-up screenings in longitudinal DR screening can be more difficult and induce lower sensitivity for both DL and HG, though the false negative rate was substantially lower for DL. Our data may be useful for health-economics analyses of longitudinal screening settings.

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