Introduction
“It’s like Rolls Royce building a full simulation of an engine, with millions of parts. They build a model and can simulate all kinds of failure and tolerance rates,” says Professor Ian Simpson.
The Edinburgh University academic is providing an analogy for digital twin technology and explaining how artificial intelligence (AI) is revolutionising healthcare.
To clarify, a digital twin is a computer model that simulates an object or process in the physical world. With the help of AI, virtual models of human hearts are built, using data from their real-world counterparts on genes, proteins, cells and whole body systems.
AI’s Historical Links to Bletchley Park
It’s a veritable technological revolution. But most people won’t know that AI in Scotland can be traced to the top-secret home of World War Two codebreakers. Indeed, the history of Scottish AI stretches back more than 60 years.
It was in 1965 that a research group was established at Edinburgh University under the leadership of Donald Michie. He’d been a member of a code-breaking group at Bletchley Park, and had worked as a cryptographer alongside Alan Turing, the famous mathematician and computer scientist.
Described as the father of British research into AI, Michie devoted his life to the development of computers to perform complex, human-like tasks.
The Gemini Project
Gemini, a pilot project which developed and tested AI for breast screenings recently finished at Aberdeen University. Researchers hope it can be used safely in hospitals, and address staff shortages and capacity issues.
Gemini is a collaboration between the University of Aberdeen, NHS Grampian, and a private company called Kheiron Medical Technologies, which created AI software called Mia.
The pilot involved analysing 220,000 mammograms from more than 55,000 people to determine how well Mia could detect breast cancers. Currently, two experts examine each mammogram and decide whether someone should be invited back for additional investigations. Similar to a human expert, Mia can examine a screening mammogram and offer an opinion, which frees up time for staff.
AI and Cancer Detection
Elsewhere in Scotland, there are other AI healthcare projects. James Blackwood, an AI expert, has worked on 65 and advises health boards on how to use AI.
He cites a number of initiatives underway: bone-fracture and lung cancer detection, breast-screening, MRI acceleration, reducing the number of deaths from stroke, and diagnosing heart failure within communities using AI – this is important, he explains, because if there are not enough scenographers in the community, “people need to be admitted into A&E to determine if they will have a heart attack.”
Concerns over AI and Data Security
There have been patients’ concerns over AI replacing humans, including fears of the loss of the emotional element of the doctor-patient relationship. Data protection is also a challenge, given AI requires large amounts of data to work accurately. There are worries over hacking and cybersecurity, privacy, and accuracy.
In 2021, researchers at Imperial College, London, found patients’ concerns over AI outweighed their perception of its benefits. The study highlighted concerns over job losses among radiologists, and over who might take responsibility, if AI gets it wrong.
AI and the Future
So, what might the future look like in 50 years time, more than a century after code-breaker Donald Michie started rolling the AI ball?
Albert King says “the spark is lit” and that “opportunities to automate AI, and release it for clinicians, nurses and front-line workers, is really really substantial”. Clarisse de Vries believes that AI used in screening is perhaps a decade away, while James Blackwood thinks we might be able to achieve “systemic AI”.
“That’s where AI is orchestrated by humans, where you tell it you need it to do this and this,” he says. “With things like ChatGPT and new technologies, what we might see in 50 years is that you will have a radiologist AI, pathologist AI or GP AI. Then you have an AI that coordinates the three different types of AI and effectively it will do a lot of the testing and diagnostic work and it will be able to present that back without anyone ever telling them to do it. This would be transformative.”
Edinburgh University certainly hopes to transform patient care, and – decades after codebreaker Michie’s work began – it remains in the vanguard of AI research.
“It’s only in the last five to 10 years that the data you need has been available,” says Professor Ian Simpson who is “very excited” about the potential of digital twins and virtual organs. “It’s very early days for that – but it’s fantastic that it’s based here.”
Additional research by Leah Flint.
Featured image credit: iStock and NicoElNino
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