CARES Funding Supports FSU CARES (Covid-19 Assessment, Research & Emerging

Science) PI: Afua O. Arhin, PhD, Fayetteville State University, Retinal Net Prototype Pilot i.e. iDetect

In collaboration with Fortem Genus, a local biomedical company, FSU piloted the development of RetinalNet .05, a prototype medical artificially intelligent system to detect COVID -19 through both retinal and iris eye imaging. 

Convolutional Neural Network COVID-19 Detection Performance Report Alpha Model 2020-12-08-23-44-42-092

In this research, a Deep-Learning algorithm is created for Covid-19 testing using eye images. The InceptionResnet CNN is used in this study. The research is well designed through the steps of preprocessing, augmentation, model optimization, learning, and results-interpretation. 

The worldwide SARS-CoV-2 pandemic has reached nearly 100 million infections and has led to more than 2.1 million deaths in more than 200 countries across the globe[1]. From the early days of the pandemic, the biggest challenge in slowing the spread of the contagion has been the paucity of screening and diagnostic tools to rapidly identify infected patients.