IAnalysing X-rays for COVID-19 using AI

WEBINAR - 13 May, 11:00-11:40 BST

An overview of the Zegami COVID-19 x-ray project

How to classify large image datasets to investigate ML models to accelerate AI development for COVID-19 identification, with the aim to create a robust diagnosis tool.

  • A cutting-edge case study of the application of AI to a real-world issue
  • Sourcing data: understanding where and how to find and prepare training data
  • How to train an ML model: approach, pitfalls, and tips on optimisation
  • Visualisation and verification of the model: applications and watch-outs

Learn about the method

interact with the people behind it

discover how it can help your own work

The Speakers

doug lawrence zegami

Doug Lawrence, BSc, Msc

Machine Learning Specialist with a background in all things science, data and machine learning, Doug is always looking for unexpected and robust ways to solve problems. 

Steve Taylor

Founder and CSO of Zegami; Co-Director, Weatherall Institute of Molecular Medicine, Oxford University

Steve’s personal mission is to disrupt the analysis of complex data to improve the world. He wants to put powerful but easy-to-use analysis methods into the hands of everyone – not just computer experts – by using innovative visualisation and interaction technologies.

steven taylor zegami

More Coverage and information on Zegami

"Artificial Intelligence that can diagnose COVID-19 using X-RAYS could help identify cases of coronavirus more quickly and predict outcomes for patients."
X-Ray Database Could be Key to Virus Fight
Explore the image collection in this interactive demo
Zegami Press Release

Easily explore large image datasets and unlock powerful insights