Diagnosis of diabetic retinopathy by artificial intelligence using smartphone

ABSTRACT

Introduction:

To obtain fundoscopy images through portable and low-cost equipment using artificial intelligence to assess the presence of DR.

Methods:

Fundus images of diabetic patients’ eyes were obtained by using a smartphone coupled to a device with a 20D lens. By using artificial intelligence (AI), the presence of DR was classified by a binary algorithm.

Results:

97 ocular fundoscopy images were evaluated (45 normal and 52 with DR). Through AI diagnostic accuracy around was 70% to 100% in the classification of the presence of DR.

Conclusion:

The approach using a low-cost portable device showed satisfactory efficacy in the screening of diabetic patients with or without diabetic retinopathy, being useful for places without infrastructure conditions.

Keywords:
Diabetes; Diabetic retinopathy; Artificial intelligence; Smartphone; Deep learning