DeepAI
Log In Sign Up

Detecting hidden signs of diabetes in external eye photographs

11/23/2020
by   Boris Babenko, et al.
11

Diabetes-related retinal conditions can be detected by examining the posterior of the eye. By contrast, examining the anterior of the eye can reveal conditions affecting the front of the eye, such as changes to the eyelids, cornea, or crystalline lens. In this work, we studied whether external photographs of the front of the eye can reveal insights into both diabetic retinal diseases and blood glucose control. We developed a deep learning system (DLS) using external eye photographs of 145,832 patients with diabetes from 301 diabetic retinopathy (DR) screening sites in one US state, and evaluated the DLS on three validation sets containing images from 198 sites in 18 other US states. In validation set A (n=27,415 patients, all undilated), the DLS detected poor blood glucose control (HbA1c > 9 operating characteristic curve (AUC) of 70.2; moderate-or-worse DR with an AUC of 75.3; diabetic macular edema with an AUC of 78.0; and vision-threatening DR with an AUC of 79.4. For all 4 prediction tasks, the DLS's AUC was higher (p<0.001) than using available self-reported baseline characteristics (age, sex, race/ethnicity, years with diabetes). In terms of positive predictive value, the predicted top 5 and a 20 generalized to dilated pupils (validation set B, 5,058 patients) and to a different screening service (validation set C, 10,402 patients). Our results indicate that external eye photographs contain information useful for healthcare providers managing patients with diabetes, and may help prioritize patients for in-person screening. Further work is needed to validate these findings on different devices and patient populations (those without diabetes) to evaluate its utility for remote diagnosis and management.

READ FULL TEXT

page 13

page 15

page 16

page 28

page 29

page 30

07/19/2022

Discovering novel systemic biomarkers in photos of the external eye

External eye photos were recently shown to reveal signs of diabetic reti...
08/10/2020

Predicting Risk of Developing Diabetic Retinopathy using Deep Learning

Diabetic retinopathy (DR) screening is instrumental in preventing blindn...
04/12/2019

Detecting Anemia from Retinal Fundus Images

Despite its high prevalence, anemia is often undetected due to the invas...
07/22/2019

Automatic detection of multiple pathologies in fundus photographs using spin-off learning

In the last decades, large datasets of fundus photographs have been coll...
03/17/2017

Computer Aided Detection of Anemia-like Pallor

Paleness or pallor is a manifestation of blood loss or low hemoglobin co...
01/26/2021

Evidence Based Prediction and Progression Monitoring on Retinal Images from Three Nations

Purpose: The aim of this work is to demonstrate how a retinal image anal...