FINANCIAL TIMES Zegami, a data visualisation spinout from Oxford University, has developed a machine learning tool that aims to diagnose
13th May, 11:00-11:40 BST Zegami has built a tool that could help speed up diagnosis of COVID-19, using a combination
Zegami has developed a new machine learning model using x-rays of Covid-19 infected lungs, artificial intelligence techniques and data visualisation tools that could help medical professionals identify corona virus cases more effectively
Our new Colour by Column feature is a powerful new dimension to visual data exploration in Zegami, enabling richer views, which reveal more of the underlying patterns in your data.
Zegami has been appointed by Oxford University researchers at the Oxford Cardiovascular Clinical Research Facility to accelerate research into cardiovascular disease.
Zegami has been collaborating with MRC Weatherall Institute for Molecular Medicines to help clean its data and assist with the training of its machine learning models, specifically around developing a better understanding of which proteins in genes bind, and where they do this in the genome.
Recently we’ve been exploring different ways to extract features from images using unsupervised machine learning techniques. Typically when wanting to get into
When making a cross-site request to an API application such as a Flask application, often there are a few roadblocks.
At Zegami we are working hard to make the ultimate experience for browsing large collections of images and visual data.
Here at Zegami we wanted to make the installation process as painless as possible for any end user of our
TechTribe Oxford talks to co-founder and chief technology officer Roger Noble about Zegami’s recent growth, scale-up plans and Twitter activity during the UK general election.
Zegami has been engaged by world famous Monterey Bay Aquarium, to strengthen its project to monitor and protect the Great White Shark Population in the Northeastern Pacific.