Ocuscreen — Diabetic Retinopathy Detection Platform

Unprecedented accuracy in diagnosis secured by AI Machine Learning

Ocuscreen — Diabetic Retinopathy Detection Platform

Unprecedented accuracy in diagnosis secured by AI Machine Learning

Ocuscreen — Diabetic Retinopathy Detection Platform

Unprecedented accuracy in diagnosis secured by AI Machine Learning

Python, PyTorch, Google cloud, Docker, Django, Qt 5, ReactJS

Challenge

Diabetic Retinopathy is a medical condition in which damage occurs to the retina due to diabetes and might lead to blindness. Proper screening can determine harmful signs of disease and prescribe treatment to slow down this process.

ENBISYS needed a solution for multiple Clients that can be used as a new software feature for ophthalmology diagnostic equipment. This feature may be easily integrated into a device circuit and may become a great competitive advantage.

The neural network was trained on 120,000+ images to achieve outstanding accuracy:
Specificity: 91%
Accuracy: 96.5%
Response time: 4 seconds

Approach

We considered various approaches that helped us build an efficient and precise AI platform to detect the signs of Diabetic Retinopathy. Our internal model was developed based on open data (EYEPACS, Messidor-1). Machine Learning is used to perform the following tasks:

Approach

We considered various approaches that helped us build an efficient and precise AI platform to detect the signs of Diabetic Retinopathy. Our internal model was developed based on open data (EYEPACS, Messidor-1). Machine Learning is used to perform the following tasks:

Approach

We considered various approaches that helped us build an efficient and precise AI platform to detect the signs of Diabetic Retinopathy. Our internal model was developed based on open data (EYEPACS, Messidor-1). Machine Learning is used to perform the following tasks: