This technology is a machine learning approach to identify patients infected with coronavirus (SARS-CoV-2) using phase-contrast images.
Current approaches to diagnose coronavirus infection are dependent on detection of the viral genome or viral antigens. These methods commonly require specialized equipment, may have low detection limits, and may not be adequately rapid. As such, an efficient and scalable approach for identifying coronavirus infection is needed to combat the epidemic.
This approach utilizes machine learning to determine whether a patient has been infected by coronavirus. The patient provides a phlegm sample, of which phase-contrast images are then taken. These images are processed by the algorithm, which is trained on infected and uninfected images, to determine if the patient’s phlegm sample is infected by coronavirus.
IR CU20262
Licensing Contact: Joan Martinez