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(910) 584-6193

STATS

For the below eye image prediction results we are using a machine learning model called an SVM (Support Vector Machine)

SENSITIVITY

=79%

SPECIFICITY

=99%

POSITIVE PREDICTIVE VALUE

=95%

NEGATIVE PREDICTIVE VALUE

=95%

Clinical Information

This section will be updated monthly or as new data becomes available.

Fayetteville
State University

FSU STUDY DEC, 2020

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. 
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University of 
North Carolina Pembroke

ASSESSMENT REPORT

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. 
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(AI) BASED COVID-19 EYE IMAGING STUDY

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.
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Fayetteville
State University

OUTCOMES AND ACCOMPLISHMENTS

There is mounting evidence that Artificial Intelligence (AI) can help the clinician in all aspects of medicine, from formulating a diagnosis to making therapeutic decisions and predicting patient outcomes. 
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iDetect Covid-19 rapid test
OFFICE LOCATION
310 Dick St. Suite D
Fayetteville NC 28301

910-584-6193
[email protected]
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