The National Health Service's Brand New Artificial Intelligence Lab!

The United Kingdom’s government has recently announced a proposal to reinvest £250 million from public funds to create an artificial intelligence laboratory which will act as the national centre to pioneer the implementation of AI into the various trusts spanning the country. It will be introduced as part of the NHSX initiative, which aims to transform digital innovation in the health service and bring about the technological changes that are currently holding back the NHS and its staff and patients by assuming responsibility in the oversight of introducing policies for technology to ensure standards are very much met. It is believed that the laboratory will oversee how artificial intelligence could aid in predicting and planning for the course of the day, how resources should be spread across departments depending on their expected needs, and assessing how patients could be allotted into hospital services and other community healthcare services depending on their needs, easing the stress on Emergency Department Triage when all hell breaks loose! It is also expected that AI could aid in other non-clinical areas such as automation in the administrative sector of healthcare, or even assessing which patients are more likely to miss an appointment and hence sending reminder messages to these patients to reduce the number of resource and timing wasting ‘no-shows’, as University College London has recently developed.. A proud Matt Hancock, the Heath Secretary under the current government, noted that artificial intelligence had an ‘enormous power to improve care, save lives and ensure doctors had more time to spend with patients’ – a statement I can very much support given the multitude of clinical inputs that AI has demonstrated in even my own articles alone. AI has shown its excellence from the insanely complex field of Ophthalmology to a similarly mind-boggling field of Radiotherapy, and we can clearly see the need to seed AI deep into the NHS’ central practises.  

A snapshot into Guangzhou Hospital’s AI lab in action, with a little critter (otherwise known as a logistics delivery bot) being used to deliver requested goods to doctors. Credit: ChinaDaily

A snapshot into Guangzhou Hospital’s AI lab in action, with a little critter (otherwise known as a logistics delivery bot) being used to deliver requested goods to doctors. Credit: ChinaDaily

As for clinical input, AI  could beneficial in many areas as we have discussed, but it has gathered the most speculation in its ability to screen for cancer (as Google’s AI has done so recently), but also highlighting which patients could be the most prone to developing certain conditions such as arrhythmia and neurodegeneration, as well as considering how given patient factors could correlate to the risk of complication in a post-operative scenario. I would argue it is somewhat futile to look at what AI can do right now, because with AI, the NHS signs up for a constantly-developing system that overcomes the main complaints of staff within hospitals, i.e. the outdated equipment and the overburdening of staff, unlike hardware, software can be updated with ease of effort and (near) nil expense, so this supports an NHS concerned about the long term. It is important to note that NHSX also encourages academia and industry come together, in the front of start-ups to induce collaborative research to drive AI innovation in a healthcare scenario, where the greatest minds can have the funding to bring about equally great changes in healthcare, in a very similar way to how inventions are made into innovations through the act of entrepreneurship  in business. This is exactly what has happened with AI expert DeepMind, who had entered a partnership with London-based NHS trust a few years ago, to develop the ‘Streams’ app that aims to manage clinical duties and has already been rolled out to various hospitals in the trust. You might have also seen how DeepMind is now using the same data to develop a model that can allow for earlier detection of acute kidney injury. These early movements in AI powered applications in healthcare are a mere morsel of what AI could achieve, but it is promising to see start-ups like Babylon Health recently announced development of a ‘chat-bot’ application for ‘triaging primary care’, which is currently being sold to some NHS hospitals.

HeartLander, the minimally invasive robot that was an early manipulation of advanced robotics to reduce the imprecision and risks of former modes of heart surgery. Credit: Carnegie Mellon University

HeartLander, the minimally invasive robot that was an early manipulation of advanced robotics to reduce the imprecision and risks of former modes of heart surgery. Credit: Carnegie Mellon University

In a press event to reveal the AI Laboratory plans, the Department of Health and Social Care said it would seek to tackle ‘some of the biggest challenges in health and care, including earlier cancer detection, new dementia treatments and more personalised care’. Other areas that could be targeted may be';

  • identifying patients at greatest risks of diseases such as heart disease, allowing for earlier diagnosis and as such a better treatment that is more likely to prevent the developing condition

  • identifying which patients are less in need of NHS hospital services, relieving stress, as patients may only require community health services

  • using predictive models to estimate future needs of beds, equipment, and drugs

  • aiding cancer screening by speeding up the results of tests, such as mammograms, brain scans, OCT scans and heart vital monitoring

  • coding systems to identify people at risk of post-operative complications, infections or requiring follow-up from clinicians, improving patient safety and reducing readmission rates

  • automating routine admin tasks ease clinician duties to help them be on ward more often with their patients, enchancing the doctor-patient relationship

  • assessing algorithms already used by the NHS to promote the standards of AI safety, making systems more logical and safe.

In fact, Simon Stevens, the chief executive of NHS England, noted that the lab’s initial focus should be placed upon individualistic NHS screening and treatments for cancer, eye disease and a range of other conditions. He had the following to say; “Carefully targeted AI is now ready for practical application in health services, and the investment announced today is another step in the right direction to help the NHS become a world leader in using these important technologies. In the first instance it should help personalise NHS screening and treatments for cancer, eye disease and a range of other conditions, as well as freeing up staff time, and our new NHS AI Lab will ensure the benefits of NHS data and innovation are fully harnessed for patients in this country.”.

Mr Matt Hancock, the Health Secretary of the United Kingdom, also had the following to say; “We are on the cusp of a huge health tech revolution that could transform patient experience by making the NHS a truly predictive, preventive and personalised health and care service. I am determined to bring the benefits of technology to patients and staff, so the impact of our NHS Long Term Plan and this immediate, multi-million pound cash injection are felt by all. It’s part of our mission to make the NHS the best it can be.The experts tell us that because of our NHS and our tech talent, the UK could be the world leader in these advances in healthcare, so I’m determined to give the NHS the chance to be the world leader in saving lives through artificial intelligence and genomics.”

The Google AI lab at Princeton University, perhaps a close resemblance to what we can expect from NHS. Credit: Princeton University

The Google AI lab at Princeton University, perhaps a close resemblance to what we can expect from NHS. Credit: Princeton University

Clearly the government is finally coming to realise the massive impact AI could have in our healthcare in the NHS. Even from my very own experience in a hospital whilst shadowing, I can tell you that doctors and nurses are seriously limited by the technology they use, not only are the computer systems slow and infuriating to use, but they also give very little support and guidance, leaving doctors prone to making mistakes and causing doctors to waste more time in making decisions that could easily be aided, if not replaced, by computerised systems powered by AI. These duties could be determining which patients are prioritised to be allotted to limited hospital beds, or go far beyond these purposes such as predicting which patients are prone of developing what conditions, after all, it is much better to prevent than to treat right? As always, testing and researcher is vital to ensure these systems can be trusted to match the expert clinical skills required in an acute medical scenario. Hence, the £250 million boost will be a welcome gift to help aid research into assessing the efficacy of AI’s input into healthcare, and could very well be baby steps for the greatest digital healthcare revolution in the United Kingdom’s history, and could yield technologies that change healthcare on a global scale! But with the growing risk of cyber-security and patient confidentiality, as we saw with The Royal Free Hospital who were heavily criticised for reusing 1.6 million patient data records with DeepMind (in the aforementioned partnership) without properly safeguarding patient data or obtaining proper consents for the use of their data. Not only this, AI can be heavily influenced by the data it is trained with, especially with respect to ancestry, so AI in genomics could be heavily affected when used to assess minorities whereas the AI’s developmental research may have been carried out on a a majorly white cohort, causing genetic differences that are open to being misinterpreted by an uninformed system. As Dr Nicola Strickland, the president of the Royal College of Radiologists, said: "I expect radiologists to be leaders in using AI algorithms to assist them, provided they can see evidence that these AI algorithms have been developed using large enough, properly curated data and rigorously validated and tested." Well put!


I would like to thank Matt Hancock, Simon Stevens, and the Department of Health and Social Services for this fantastic news. Although we have no immediate developments to note as of yet, there is no telling what this laboratory could achieve in the near future. A kind ‘good luck’ to all the researchers and academia who will be responsible for forming the NHS of tomorrow. Thank you for your reading.


Thumbnail: Displaying the future of healthcare technology, SmartKem: http://smartkem.com/displaying-future-healthcare-technology/