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Associate Professor of Engineering Science
University of Oxford
The Institute of Cancer Research
Anaesthetic and Critical Care Doctor, Machine Learning Researcher
Lecturer, Medical Image Computing
Imperial College London
Scientists have developed a new test that can pick out women at high risk of relapsing from breast cancer within 10 years of diagnosis. Their study looked for immune cell ‘hotspots’ in and around tumours, and found that women who had a high number of hotspots were more likely to relapse than those with lower numbers. The new test could help more accurately assess the risk of cancer returning.Read More
AI technology that is capable of analysing and interpreting medical scans with super-human performance will be the focus of ERC funded research carried out by Dr Ben Glocker, from the Department of Computing. Dr Glocker and his team aim to develop AI technology based on machine learning that can sift through the mountain of data to provide detailed insights into complex diseases.Read More
Last year Cera was identified as one of 50 of the freshest and most inspiring digital companies using technology and innovation to shake up their sectors in City A.M.'s Digital Innovators Power List. Following a public vote and after careful consideration by supporting partners and judges, it was named as one of the top 10 Digital Innovators.Read More
Discover advances in deep learning tools and techniques from the world's leading innovators across industry, academia and the healthcare sector. Learn from the experts in speech & text recognition, neural networks, image classification and machine learning.
The summit will showcase the opportunities of advancing methods in deep learning and their impact across healthcare & medicine. Discover the deep learning tools & techniques set to revolutionise healthcare applications, medicine & diagnostics from a global line-up of experts.
A unique opportunity to interact with industry leaders, data scientists, founders, CTOs and healthcare professionals leading the deep learning revolution. Learn from & connect with 200+ innovators sharing best practices to advance the deep learning in healthcare revolution.