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

The Speakers

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.

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."