Artificial intelligence (AI) and deep learning (DL) can predict which patients with diabetic retinopathy (DR) will progress the fastest based on a single color fundus photograph, researchers say.
Arcadu et al. said their results “highlight the importance of the predictive signal located in the peripheral retina fields, not routinely collected for DR assessments, and the importance of microvascular abnormalities.”1
In-person expert examinations are impractical and unsustainable given the pandemic size of the diabetic population. As such, AI may offer a solution to this conundrum. DL, and specifically, deep convolutional neural networks (DCNNs), can be used for an end-to-end assessment of raw medical images to produce a target outcome prediction, the authors wrote.
1. Arcadu F, Benmansour F, Maunz A, et al. Deep learning algorithm predicts diabetic retinopathy progression in individual patients. NPJ Digit Med. 2019;2:92.
2. Obeid A, Gao X, Ali FS, et al. Loss to follow-up in patients with proliferative diabetic retinopathy after panretinal photocoagulation or intravitreal anti-VEGF injections. Ophthalmology. 2018;125:1386-1392.