A deep learning system for predicting time to progression of diabetic retinopathy
Shanghai Jiao Tong University · Shanghai Sixth People's Hospital · +24 more institutions
Abstract
Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. The risk of DR progression is highly variable among different individuals, making it difficult to predict risk and personalize screening intervals. We developed and validated a deep learning system (DeepDR Plus) to predict time to DR progression within 5 years solely from fundus images. First, we used 717,308 fundus images from 179,327 participants with diabetes to pretrain the system. Subsequently, we trained and validated the system with a multiethnic dataset comprising 118,868 images from 29,868 participants with diabetes. For predicting time to DR progression, the system achieved concordance indexes of 0.754-0.846 and…
Citation impact
- FWCI
- 109.28
- Percentile
- 100%
- References
- 62
Authors
52- LDLing Dai
Shanghai Jiao Tong University, Shanghai Sixth People's Hospital
- BSBin ShengCorresponding
Shanghai Jiao Tong University, Shanghai Sixth People's Hospital
- TCTing‐Li Chen
Huadong Hospital, Huadong Sanatorium
- QWQiang Wu
Shanghai Jiao Tong University, Shanghai Sixth People's Hospital
- RLRuhan Liu
Shanghai Jiao Tong University, Shanghai Sixth People's Hospital
Topics & keywords
- Medicine
- Diabetic retinopathy
- Concordance
- Blindness
- Diabetes mellitus
- Fundus (uterus)
- Ophthalmology
- Artificial intelligence