An automatic AI system developed by Alder Hey clinicians and researchers from the Universities of Manchester and Liverpool have received a £1.2 million grant from the NIHR Invention for Innovation programme.
The system automates x-ray interpretation, data capture, and monitoring, with an AI algorithm trained on thousands of x-ray images that is capable of locating hip bone outlines and detecting cases where dislocation is beginning to happen. In testing, Alder Hey reports that it has performed similarly to human medical experts in terms of accuracy, whilst taking “a fraction of the time” on the analysis.
Professor Daniel Perry, a surgeon at Alder Hey Children’s NHS Foundation Trust, said: “AI will revolutionise the care we provide, enhance diagnostics and care pathways and free up time for our clinicians to do what they do best: caring for our children and young people. This is a great example – a practical tool directly focused on better care for children with cerebral palsy.”
Manchester Imaging Ltd will now look to take the AI algorithm and build it into a medical device to be integrated into hospital systems, with the intention of making it easier for clinicians to use in identifying where preventative intervention is needed.
According to Alder Hey, using the tool to process thousands of images will enable x-ray data to be automatically entered into the Cerebral Palsy Integrated Pathway database, supporting new research to better understand the disease and its monitoring.
Professor Timothy Cootes, a researcher on the project, spoke of hopes that the automation of the process will help boost standardisation and ensure that the Cerebral Palsy Integrated Pathway can be “fully integrated throughout the NHS”.
Wider trend: AI in health and care
HTN was joined by Neill Crump, digital strategy director at The Dudley Group NHS Foundation Trust, and Lee Rickles, CIO at Humber Teaching NHS Foundation Trust, to discuss practical steps health and care organisations can take to prepare for AI. Neill and Lee shared details of their current work and their journey to date, best practices, learnings, challenges, and the opportunities that lie ahead.
The Medicines and Healthcare products Regulatory Agency has issued a call for evidence on the regulation of AI in healthcare, asking members of the public, clinicians, industry, and healthcare providers to share their views on the modernisation of AI rules, keeping patients safe as AI evolves, and the distribution of responsibilities between regulators, companies, healthcare organisations, and individuals. In particular, views are sought on the UK’s current framework for regulating AI in healthcare and how it may need to be improved to “ensure fast access to safe and effective AI medical devices”, as well as on approaches to check safety once AI medical devices are in use, and how responsibility and liability are split between different parties involved in their deployment.
The co-founder of health data startup, Torch, has shared that the company has been acquired by OpenAI for a sum of “$100m+”. Outlining the mission to provide healthcare “for a billion people, for free”, Aoun says integrating that work into the AI used by billions every day “makes that dream a reality”. According to the Torch website, the startup is focused on connecting health data from a wide range of sources and offering answers to common health questions using AI.
