Our world is increasingly connected and species must rely on one another for food, protection, and life. However, farmers, governments, veterinarians, doctors, and citizens across the globe face the threat of parasites. From waterborne to gastrointestinal, parasites invade our food and water sources, harm crop production, and cause diseases. QMIRA™ is training Artificial Technology to test, diagnose, and intervene in this global issue. As a result, we will have less need to use medications, chemicals, and harsh treatments designed to intervene in parasitic infections and diseases.
QMIRA™ provides a platform capable of identifying variances in biological systems via quantitative microscopic image analysis. The mission of QMIRA™ is to provide low-cost diagnostic solutions to common infectious and parasitic disease using Artificial Intelligence for microscopy. By using innovative microscopic image recognition algorithms with a low-cost automated microscope, QMIRA™ is able to provide higher accuracy and efficiency in the diagnostic process.
We’ve developed Artificial Intelligence specifically trained to find and diagnose intestinal parasites so tiny and translucent that they typically go unnoticed, unless the sample is sent to a lab.
Farmers around the world lose crops to soil dwelling parasites. Our Artificial Intelligence allows those farms to stop treating every single plant and helps farmers diagnose the infection before symptoms ever surface.
Food is tested every day for parasites and other contaminations. Our comprehensive testing methods allow food producers to reduce the time and costs associated with testing their products.
Our focus on marine biology led us to develop Artificial Intelligence capable of testing drinking water to help eliminate disease around the world.
Millions of people around the world suffer because of parasites that cause diseases like malaria. In an effort to reduce the number of people suffering, our Artificial Intelligence can find and diagnose diseases found in human bodily fluids.
Working with technology partners, we’ve developed an innovative microscopic image recognition algorithm that is finely tuned to diagnose the smallest of parasites with extreme accuracy.