MUNICH: KING'S COLLEGE LONDON (KCL) will adopt Nvidia's AI tech to deliver souped-up radiology and pathology services to NHS patients across the UK.
The partnership, which was announced at GTC Europe on Wednesday, will see KCL make use of Nvidia's new DGX-2 supercomputer and Clara supercomputing platform to improve the accuracy and speed of its services.
Radiology is one area of focus for KCL and Nvidia. With the amount of imaging that has to be carried out increasing 16 per cent year on year, yet the number of radiologists increasing by just one per cent, specialists now only have around three to four seconds to analyse each image, down from 20 to 30 seconds.
With DGX2, which packs 2 petaflops of computing power and 512GB HBM2 memory, KCL will be able to better tackle the training of large, 3D datasets, which Nvidia boasts will now take "minutes, rather than days".
KCL will roll out this tech, which will also use AI to offer up more detailed, 3D images, along with Nvidia's Clara supercomputing platform to four hospitals - King's College Hospital, Guy's and St Thomas', and South London and Maudsley - with the aim of improving treatmenet for eight million NHS patients.
At these hospitals, Nvidia and KCL will also co-locate researchers and engineers with clinicians in a bid to accelerate the discovery of critical data strategies, targeted AI problems and speed deployment in the clinic.
"This is a huge opportunity to transform patient outcomes by applying the extraordinary capabilities of AI to ultimately make diagnoses earlier and more accurately than in the past," said Professor Sebastien Ourselin, head of the School of Biomedical Engineering and Imaging Sciences at KCL.
In Blighty, the NHS has also teamed with Google's DeepMind to better diagnose ocular diseases. The AI wrangler worked with Moorfields Eye Hospital and University College London to create a deep learning system that identifies common eye diseases by analysing 3D scans of patient's eyes. After that, it then recommends treatment for those with ocular afflictions. µ
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