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
A deep learning, cloud-based API that can read lateral flow test results beyond the human visible spectrum.
Assists users and health professionals to perform diagnostic tests and share results. Available as an Android, iOS or web application.
Test To Go by Excalibur Healthcare Services reads Excalibur Rapid SARS-CoV-2 Antigen Test results rapidly, reliably and accurately.
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.
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.
Reduces the variability, subjectivity and possible error associated with manual, unassisted image reading.
Analysis of large image datasets may help inform disease and public health management.
Results are returned in under 2 seconds, and available for analysis immediately, improving user adoption and supporting decision making.
Data is encrypted and securely held in the cloud with robust cyber security.
MagnifEye is aimed at
Diagnostic test providers and manufacturers requiring faster, more accurate reporting of test results.
Public health agencies requiring rapid, accurate test reporting and analysis for epidemiological insights.
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