Zegami has built a tool that could help speed up diagnosis of COVID-19, using a combination of deep learning and groundbreaking data visualisation. This platform has shown proficiency, using a limited dataset, in distinguishing between x-rays of COVID-19 infections and infections caused by viral or bacterial pneumonia, as well as images of healthy lungs. COVID-19 Xray data was sourced from the Github data initiative, launched by Joseph Paul Cohen. Postdoctoral Fellow, Mila, University of Montreal. It seeks to grow the world’s largest collection of X-ray and CT images of COVID-19 infected lungs to enable automated medical diagnosis.
Oesophageal cancer video frames to find cancer lesions to train the machine learning model.
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