AI will transform healthcare delivery and improve patient outcomes, but currently there are too many barriers that hinder its accelerated adoption at scale.
These include the speed at which AI models are traditionally deployed and the complexities presented by training models in an ethical and secure way.
But, there’s an answer to both.
In this session, you’ll hear about the experience the speakers have gained at the NHS’s AI Centre for Value Based Healthcare and learn directly from those helping drive the change needed to overcome the barriers of scaling AI deployment in healthcare.
You will learn how NHS trusts are using the AI Deployment Engine (AIDE) to implement AI models within radiology and other clinical workflows in a matter of weeks, rather than years. And, how those healthcare organisations will use the Federated Learning Interoperability Platform (FLIP) to train models on large data sets securely within their own environments, removing the compliance headaches of transferring and sharing sensitive patient data.
This technology is ready to scale now and available for AI model researchers, healthcare providers and AI companies to accelerate adoption.
During this talk, colleagues from the AI Centre, leading NHS trusts deploying the technology, and the solutions’ architects Answer Digital will answer critical questions, such as:
– How can healthcare organisations overcome barriers to developing AI models quickly and safely?
– How can AI be implemented into radiology workflows with one-click deployment?
– Why are automated deployment engines and federated learning needed to unlock AI at scale?
– How can NHS digital leaders create the right foundations to maximise the £21m national funding available for rolling out new AI solutions?
– What can we learn from existing radiology use cases and what’s still to come?
This event is in-person and live-streamed.
We have two ticket types set up on Eventbrite so you can book either in-person or online attendance.
Dial in details will be shared closer to the time of the event.