A deep-learning algorithm increased the accuracy of reading images for detecting retinal pathologies in patients with diabetes.
The study demonstrated the beneficial effects of computer-assisted reading of images.
“Overall, we saw that computer assistance in this study actually help improve the five-class diagnostic accuracy,” Dr. Rahimy said. “This improvement was really driven by cases in which there was pathology.
“When DR was present, we saw a substantial improvement by having graded assistance as well as the graders and the heatmaps together,” Dr. Rahimy added.
A noteworthy study finding was that improvement depended on the background of the reader.
Results showed that when general ophthalmologists read the images unassisted, the level of accuracy was not as high as the level of the algorithm. When general ophthalmologists were assisted by grades provided by the algorithm and by both the grades and heatmaps, their accuracy levels improved to the level of the algorithm, he pointed out.
When performances of the retina specialists were evaluated, they were seen to have met the level of the algorithm, but in the scenarios when grades and the grades plus heatmaps were added, the retina specialists exceeded the accuracy level of the algorithm.
The sensitivity increased as a result of the computer assistance.
Ehsan Rahimy, MD
E: [email protected]
Dr. Rahimy is a physician consultant to Google.