MagnifEye allows standardisation of test reporting, thereby increasing confidence in LFD testing, reducing user error and increasing overall accuracy of an AI LFD programme.1
AI-powered reading and analysis of diagnostic tests
The COVID-19 pandemic has increased the need for accurate reading of point-of-care diagnostic tests for clinical decision support and disease surveillance across large populations.
MagnifyEye utilises Sensyne’s expertise in developing novel deep learning approaches and AI algorithms to automate and improve the accuracy of reading diagnostic tests across a wide range of indications including COVID-19.
MagnifEye API
A deep learning, cloud-based API that can read lateral flow test results beyond the human visible spectrum.
MagnifEye COVID app
Assists users and health professionals to perform diagnostic tests and share results. Available as an Android, iOS or web application.
Test to Go
Powered by MagnifEye
Test To Go by Excalibur Healthcare Services reads Excalibur Rapid SARS-CoV-2 Antigen Test results rapidly, reliably and accurately.
Potential benefits
Improves reading accuracy and consistency
Reduces the variability, subjectivity and possible error associated with manual, unassisted image reading.
Epidemiological insight
Analysis of large image datasets may help inform disease and public health management.
Speed and flexibility
Results are returned in under 2 seconds, and available for analysis immediately, improving user adoption and supporting decision making.
Secure
Data is encrypted and securely held in the cloud with robust cyber security.
A proven tested technology
NHS Digital conducted a pilot study in April 2021 that tested MagnifEye on over 100,000 real world cases. The results of the pilot study1 show:
MagnifEye increased sensitivity (the ability to identify positive tests correctly) to 97.6% and specificity (the ability to identify negative tests correctly) to 99.99% in reading lateral flow tests, as compared to a human reader.
Results
A significant proportion of positive cases that were previously missed by users or trained lateral flow test readers were detected by MagnifEye. At Assisted Testing Sites (ATSs) the algorithm identified 24.4% of true positive tests that were missed by trained operators.
Ongoing use of this algorithm is anticipated to support the Government in identifying positive cases with low viral loads which might otherwise be missed via human read and improve objective reading of tests by supporting the visually impaired or anxious in interpretation of their COVID lateral flow results.
MagnifEye is aimed at
Diagnostic test providers and manufacturers requiring faster, more accurate reporting of test results.
