New Deep-Learning Model Helps the Automated Screening of Common Eye Disorders
Photo: Tohoku University
Automation in disease diagnosis is reliant on deep learning models that can accurately and efficiently identify measurements of tumors, tissue volume, or other sorts of abnormalities. Now, researchers from Tohoku University have unveiled a new, resource-light model capable of identifying many common eye diseases.
A new deep learning (DL) model that can identify disease-related features from images of eyes has been unveiled by a group of Tohoku University researchers. This "lightweight" DL model can be trained with a small number of images, even ones with a high-degree of noise, and is resource-efficient, meaning it is ...