Scientists have developed an extremely rapid diagnostic test that detects and identifies viruses in less than five minutes.
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Researchers havee repurposed robotic technology normally used for synthetic biology research to help with testing for COVID-19.
A new app that helps patients in self-isolation monitor for symptoms of COVID-19 and identify their mental health needs has been developed.
The Fraunhofer Institutes project M³Infekt aims to develop a multi-modal, modular and mobile system of sensors for monitoring infectious diseases.
By analyzing Fitbit data and self-reported symptoms, researchers analyzed trends in heart rate, step count, and symptom duration between patients with flu and those with COVID-19.
Machine learning can be used to fill a significant gap in Canadian public health data related to ethnicity and Aboriginal status, according to research by a University of Alberta research epidemiologist.
Scientists are launching a project to apply machine learning methods to assess the role of climate variables in disease transmission
A portable surveillance device powered by machine learning can detect coughing and crowd size in real time, then analyze the data to directly monitor flu-like illnesses trends.