The AI Diagnostic Fund will allow NHS Trusts to apply for funding to expedite the deployment of AI imaging and decision support tools, particularly for diagnosing conditions such as cancers, strokes, and heart conditions.

The Health and Social Care Secretary, Steve Barclay, has also pledged to implement AI stroke-diagnosis technology across all stroke networks by the end of 2023, a significant increase from the current 86 percent. This initiative aims to facilitate faster treatment for thousands of stroke patients.

Barclay emphasised the transformative impact of AI on healthcare and its ability to improve patient care and reduce waiting times.

As of April 2023, there were 7.42 million people waiting for treatment on the NHS waiting list in England. This is the highest number of people waiting for treatment since records began in 2004.

Of these patients, nearly 3.09 million were waiting over 18 weeks, and around 371,000 were waiting over a year for treatment. The median waiting time for treatment was 13.8 weeks – almost double the pre-COVID median wait of 7.2 weeks in April 2019.

One of the primary applications of the AI Diagnostic Fund is the use of AI tools for analysing chest X-rays, a common diagnostic tool for lung cancer, which is the leading cause of cancer-related deaths in the UK.

With over 600,000 chest X-rays performed each month in England, the widespread deployment of AI tools to NHS Trusts will aid clinicians in early cancer detection, ultimately improving patient outcomes.

The integration of AI in the NHS has already demonstrated positive results, such as reducing the time it takes to diagnose and treat stroke victims. By enabling faster stroke diagnosis, AI has been shown to triple the chances of patients living independently after a stroke.

Sridhar Iyengar, Managing Director of Zoho Europe, said:

“Artificial Intelligence is set to play a crucial role in the future of many industries, including digital healthcare. It could enable doctors and nurses to make faster, more accurate decisions.

Key to its continued success is building trust with the public, ensuring the highest standards of data management, to protect the privacy of patients.

Deployed correctly, AI can save time and money. This is something that is already seen in many private sector businesses across the UK and public services can benefit from following suit.”

The funding provided through the AI Diagnostic Fund will be available to support the implementation of any AI diagnostic tool that NHS Trusts wish to deploy. However, the proposals must demonstrate value for money to receive approval.

The government has already invested £123 million in 86 AI technologies, benefiting patients through improved stroke diagnosis, screening, cardiovascular monitoring, and home-based condition management.

The introduction of AI into healthcare aligns with the NHS’s mission to adopt the latest proven technology to enhance patient care and provide value for taxpayers.

Dr Katharine Halliday, President of the Royal College of Radiologists, said:

“At a time when diagnostic services are under strain, it is critical that we embrace innovation that could boost capacity – and so we welcome the Government’s announcement of a £21 million fund to purchase and deploy AI diagnostic tools.

All doctors want to give patients the best possible care. This starts with a timely diagnosis, and crucially, catching diseases at the earliest point. There is huge promise in AI, which could save clinicians time by maximising our efficiency, supporting our decision-making and helping identify and prioritise the most urgent cases.

Together with a highly trained and expert radiologist workforce, AI will undoubtedly play a significant part in the future of diagnostics.”

To ensure the safe deployment of AI devices, the government recently established the AI & Digital Regulation Service, which assists NHS staff in accessing the necessary information and guidance. This service simplifies the understanding of AI regulations in the NHS, enabling developers and adopters of AI to bring their products to market more efficiently.

The investment in AI technology is crucial, considering that the NHS currently spends £10 billion annually on medical technology, and the global market is projected to reach £150 billion next year. Access to innovative technologies promises significant benefits for patients, including disease prevention, early diagnosis, effective treatments, and faster recovery.

Dr Antonio Espingardeiro, IEEE member, software and robotics expert, commented:

“As it becomes more sophisticated, AI can efficiently conduct tasks traditionally undertaken by humans, the potential for the technology within the medical field is huge. It can analyse vast quantities of information, and when coupled with machine learning, search through records and infer patterns or anomalies in data, that would otherwise take decades for humans to analyse.

We are just starting to see the beginning of a new era where machine learning could bring substantial value and transform the traditional role of the doctor. The true capabilities of this technology as an aide to the healthcare sector are yet to be fully realised.

In the future, we may even be able to solve of some of the biggest challenges and issues of our time. With the increased adoption of AI and robotics, we will soon be able to deliver the scalability that the healthcare sector needs and establish more proactive care delivery.”

With the support of AI, NHS staff can look forward to enhanced capabilities in diagnosing and treating patients, leading to improved healthcare outcomes and a more efficient healthcare system overall.

(Photo by Ian Taylor on Unsplash)

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The National Institute for Health and Care Research (NIHR) is contributing more than £1 million in funding to develop the new technology, which is known as Organ Quality Assessment (OrQA). It works in the same way as Artificial Intelligence-based facial recognition to evaluate the quality of an organ.

It is estimated the technology could result in up to 200 more patients receiving kidney transplants and 100 more receiving liver transplants a year in the UK.

Colin Wilson, transplant surgeon at Newcastle upon Tyne Hospitals NHS Foundation Trust and co-lead of the project, said: “Transplantation is the best treatment for patients with organ failure, but unfortunately some organs can’t be used due to concerns they won’t function properly once transplanted.

“The software we have developed ‘scores’ the quality of the organ and aims to support surgeons to assess if the organ is healthy enough to be transplanted.

“Our ultimate hope is that OrQA will result in more patients receiving life-saving transplants and enable them to lead healthier, longer lives.”

Professor Hassan Ugail, director of the Centre for Visual Computing at the University of Bradford, whose team is working on image analysis as part of the research, said: “Currently, when an organ becomes available, it is assessed by a surgical team by sight, which means, occasionally, organs will be deemed not suitable for transplant.

“We are developing a deep machine learning algorithm which will be trained using thousands of images of human organs to assess images of donor organs more effectively than what the human eye can see.

“This will ultimately mean a surgeon could take a photo of the donated organ, upload it to OrQA and get an immediate answer as to how best to use the donated organ.”

There are currently nearly 7,000 patients awaiting organ transplant in the UK. An organ can only survive out of the body for a limited time. In most cases, only one journey from the donor hospital to the recipient hospital is possible. This means it is essential that the right decision is made quickly.

The project is being supported by NHS Blood and Transplant (NHSBT), Quality in Organ Donation biobank and an NIHR Blood and Transplant Research Unit to deliver research for the NHS. It also involves academics from the Universities of Oxford and New South Wales.?

Professor Derek Manas, medical director of NHSBT Organ Donation and Transplantation, said: “This is an exciting development in technological infrastructure that, once validated, will enable surgeons and transplant clinicians to make more informed decisions about organ usage and help to close the gap between those patients waiting for and those receiving lifesaving organs. We at NHSBT are extremely committed to making this exciting venture a success.”

Health Minister Neil O’Brien said: “Technology has the ability to revolutionise the way we care for people and this cutting edge technology will improve organ transplant services. Developed here in the UK, this pioneering new method could save hundreds of lives and ensure the best use of donated organs.

“I encourage everyone to register their organ donation decision. Share it with your family so your loved ones can follow your wishes and hopefully save others.”

Chief executive of the NIHR Professor, Lucy Chappell, said: “Funded by our Invention for Innovation Programme, this deep machine learning algorithm aims to increase the number of liver and kidney donor organs suitable for transplantation. This is another example of how AI can enhance our healthcare system and make it more efficient. Once clinically validated and tested, cutting edge technology such as this holds the real promise of saving and improving lives.”

‘Proof of concept’ work has been carried out in liver, kidney and pancreas transplantation as well as at an advanced stage of pre-clinical testing in liver and kidney.

It is hoped the OrQA software will be ready for a licensing study within the NHS within two years. There is also the possibility of marketing the tool worldwide.

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Brits have become used to long NHS wait times for many years. However, the post-covid backlog has sent the number of patients on waiting lists rocketing:

There are many strong views on what NHS reforms are needed, but one thing everyone can agree on is that the current trajectory is unsustainable. Modern technologies will be vital in delivering the improvements that will help both NHS staff and patients.

The Walton Centre NHS Foundation Trust has announced a partnership with TCS to develop digital solutions that increase the productivity of specialists, reduce waiting times for patients, and improve the overall experience. 

Shalini Mathur, Business Unit Head of Public Services for the UK, Europe, and ANZ at TCS, said:

“We are pleased to partner with The Walton Centre to transform patient care in the UK using next-gen technologies.

These technologies and solutions will help reduce waiting times for patients while improving the productivity of specialist consultants. This creates a blueprint for similar digital innovation in other clinical settings.”

The first product of this partnership is an AI chatbot that aims to transform how patients with headaches are diagnosed and treated.

A headache can range from nothing serious to being potentially fatal or life-changing. Anyone who is concerned their headache could be out-of-the-ordinary should get it checked out, but deciding which patients should be prioritised is a critical but difficult task.

Patients with headaches make up the largest number of outpatient referrals to neurologists at The Walton Centre. The use of a chatbot will enable information about the patient’s condition to be collected in order to compile a detailed report for clinicians to review before an initial appointment.

Dependent on the clinician’s assessment, a patient may be put on a fast track for an examination or offered guidance on alleviating symptoms while they wait for their turn.

Dr Anita Krishnan, Divisional Clinical Director for Neurology at The Walton Centre, and a Consultant Neurologist specialising in headaches, commented:

“Technology is a huge part of medicine and it’s exciting to work with TCS to create a new artificial intelligence-based solution which will help our patients.

The chatbot system also has the potential to be extended into other areas of medicine, which could benefit even more patients.

We are working closely with TCS and our other specialist partners to ensure the new solution is effective and safe and improves efficiency and patient outcomes.”

While it’s a fairly limited trial to begin with, AI-powered chatbots could make a real difference across the NHS. Chatbots can help to ensure that patients are correctly prioritised and less of the scarce time consultants have available is spent having to ask the questions for information that can be collected beforehand.

Chatbots aren’t going to solve all of the NHS’ problems, but they should make a positive difference for staff and patients.

(Photo by Nicolas J Leclercq on Unsplash)

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Breakthroughs in medical AIs are helping to reduce patient suffering, the likelihood and/or severity of long-term complications, and even save lives across a number of ailments.

Some of the benefits from medical AI breakthroughs are achieved through improved understanding leading to better treatment, while others are due to reducing the amount of time healthcare professionals have to spend on repetitive tasks.

Over 100,000 people in the UK suffer from a stroke per year; with over 32,000 deaths as a result. NHS SBS sought out how AI can help tackle one of the UK’s leading causes of death and disability.

Adam Nickerson, NHS SBS Senior Category Manager – Digital & IT, said:

“This use of AI is a prime example of how new technologies have the potential to transform NHS patient care, speeding up diagnosis and treatment times by ensuring that expert clinical resource is targeted where it has the greatest impact for the patient. 

By identifying areas in which technology can be used to help speed up patient pathways, clinicians have more time for providing personalised care and patient waiting lists – exacerbated by the pandemic, are reduced.

We have been pleased to work alongside some of the country’s leading tech minds, expert stroke clinicians, and policy leaders to develop this unique framework, which will go a long way to enabling more rapid uptake of Stroke AI software across the NHS.”

While AI can be a powerful tool in medicine, it can be difficult to ensure solutions are evidence-based and cost-effective. That’s where the new ‘Provision of AI Software in Neuroscience for Stroke Decision Making Support’ procurement framework comes in.

The framework was developed with contributions from across NHS England and NHS Improvement (NHSEI), clinical leads from the 20 Integrated Stroke Delivery Networks across England, the Academic Health Science Network, and with further input from NHSX and the Care Quality Commission.

Darrien Bold, National Digital and AI Lead for Stroke at NHSEI, commented:

“We are already seeing the impact AI decision-support software is having on stroke pathways across the country, and the introduction of this framework will drive forward further progress in delivering best-practice care where rapid assessment and treatment are of the essence.

Over the past 18 months, the heath and care system has been compelled to look to new technologies to continue providing frontline care, and the stroke community has embraced new ways of working in times of unprecedented pressure.

This framework agreement will be of great benefit as we implement the NOSIP – driving better outcomes, better patient experience and better patient safety, using new technology quickly, safely and innovatively.”

Time is very much of the essence when it comes to strokes. The framework will enable the procurement of AI solutions that analyse images to detect ischaemic or haemorrhagic strokes and provide real-time interpretations to augment the review, diagnosis, and delivery of time-dependent treatments.

While manual review of imagery can take up to 30 minutes to interpret, AI is able to do so within seconds.

“Rapid brain imaging and its interpretation is arguably one of the most important steps in the care of patients with stroke-like symptoms,” commented Dr David Hargroves, Getting It Right First Time (GIRFT) Clinical Lead for Stroke and National Specialty Advisor for Stroke Medicine at NHSEI.

“Incorporating AI decision support software is likely to improve access to disability-saving interventions to thousands of patients. This framework agreement supplies a valuable platform to support providers of hyperacute stroke care in the purchase of AI software.”

As part of the NHS Long Term Plan, the health service aims to achieve a tenfold increase in the proportion of stroke victims who receive a thrombectomy by 2022—estimated to enable around 1,600 more patients per year to live independently.

AI will be key to achieving the NHS’ long-term goals across care for stroke patients and more. We look forward to seeing all the ways health services around the world put AI to good use over the coming years to improve patient outcomes.

(Photo by Ian Taylor on Unsplash)

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Racial inequality continues to be rampant in healthcare. Examining the fallout of COVID-19 serves as yet another example of the disparity between ethnicities.

In England and Wales, males of Black African ethnic background had the highest rate of death involving COVID-19, 2.7 times higher than males of a White ethnic background. Females of Black Caribbean ethnic background had the highest rate, 2.0 times higher than females of White ethnic background. All ethnic minority groups other than Chinese had a higher rate than the White ethnic population for both males and females.

Such disparities are sadly common across many conditions that can reduce life enjoyment, limit opportunities, and even lead to premature death. AI could be a powerful aid in tackling the problem, if thoroughly tested and implemented responsibly.

“As the first health and social care secretary from an ethnic minority background, I care deeply about tackling the disparities which exist within the healthcare system,” explained Javid, speaking to The Guardian.

Among the projects given the green light by Javid include the creation of new standards for health inclusivity to improve the representation of ethnic minorities in datasets used by the NHS.

“If we only train our AI using mostly data from white patients it cannot help our population as a whole,” added Javid. “We need to make sure the data we collect is representative of our nation.”

A recent analysis found a significant disparity in performance when using computer screening to detect diabetic retinopathy in patients from ethnic minority communities due to different levels of retinal pigmentation. One project will attempt to address this disparity.

Among the devastating statistics affecting minority communities is that black women are five times more likely to die from complications during pregnancy than white women. One project will use algorithms to investigate the factors and recommend changes – including potentially new training for nurses and midwives – that will hopefully ensure that everyone has the best possible chance to live a healthy life with their child.

The development of an AI-powered chatbot also hopes to raise the uptake of screening for STIs/HIV among minority ethnic communities.

The drive will be led by NHSX. A report in 2017 by PwC found that just 39 percent of the UK public would be willing to engage with AI for healthcare. However, research (PDF) by KPMG found that – despite an overall unwillingness from the British public to share their data with the country’s biggest organisations even if it improved service – the NHS came out on top with 56 percent willing to do so.

If the UK Government wants to use AI as part of its “level up” plans, it will need to tread carefully with a sceptical public and prove its benefits while avoiding the kind of devastating missteps that have cost thousands of lives and defined Johnson’s premiership so far.

(Image Credit: UK Parliament under CC BY 3.0 license)

Find out more about Digital Transformation Week North America, taking place on 9-10 November 2021, a virtual event and conference exploring advanced DTX strategies for a ‘digital everything’ world.

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Google-owned DeepMind was quietly given the personal records of 1.6 million patients at the Royal Free London NHS Foundation Trust.

DeepMind said that it was using the data to create a potentially life-saving app called Streams. The app was designed to alert, diagnose, and detect when patients were at risk of developing acute kidney injury. It’s currently in the process of being decommissioned.

Several investigations were launched, including by the Information Commission that said in 2017 the hospital had not done enough to protect the privacy of patients when it shared data with Google.

Following that ruling, DeepMind apologised and said that it should have been thinking about the needs of patients rather than on building tools for clinicians.

The new case is being handled by law firm Mishcon de Reya on behalf of the lead plaintiff Andrew Prismall and the over 1.5 million other affected patients.

Mr Prismall said: “Given the very positive experience of the NHS that I have always had during my various treatments, I was greatly concerned to find that a tech giant had ended up with my confidential medical records.

“As a patient having any sort of medical treatment, the last thing you would expect is your private medical records to be in the hands of one of the world’s biggest technology companies.

“I hope that this case will help achieve a fair outcome and closure for all of the patients whose confidential records were obtained in this instance without their knowledge or consent.”

In the UK, such cases are “opt-out” which means all impacted parties will be included in the action unless they specifically request not to be. Given the size of the action, the overall payout for DeepMind could be large but small for each individual.

The case is just one of a growing number of high-profile cases around data collection in recent years. In April, Anne Longfield, the former Children’s Commissioner for England, filed a case against TikTok on behalf of millions of UK children over how the app collected and used their data.

Data collection is vital for training AIs that could very well save lives. However, individual privacy is also important.

Mishcon Partner Ben Lasserson, who is leading the DeepMind case, said: “This important claim should help to answer fundamental questions about the handling of sensitive personal data and special category data.

“It comes at a time of heightened public interest and understandable concern over who has access to people’s personal data and medical records and how this access is managed.”

As the UK leaves the EU it is looking to change its data laws. While the EU’s laws have often been criticised as being too strict and leaving innovation to happen outside of Europe, there are concerns that the UK could become too relaxed despite ministers’ pledges not to.

“There’s an opportunity for us to set world-leading, gold standard data regulation which protects privacy, but does so in as light-touch a way as possible,” said Culture Secretary Oliver Dowden.

Britain’s data watchdog is also getting a shakeup and will be led by John Edwards, New Zealand’s current privacy commissioner.

“There is a great opportunity to build on the wonderful work already done and I look forward to the challenge of steering the organisation and the British economy into a position of international leadership in the safe and trusted use of data for the benefit of all,” commented Edwards.

Only time will tell if the UK manages to strike a balance between the strictness of the EU and the somewhat laissez-faire approach taken by many of the world’s powers. However, the cases against DeepMind and others show that a modernisation of laws and thinking is needed to unlock the potential of AI to improve/save lives while protecting individual privacy.

(Photo by Tugce Gungormezler on Unsplash)

Find out more about Digital Transformation Week North America, taking place on 9-10 November 2021, a virtual event and conference exploring advanced DTX strategies for a ‘digital everything’ world.

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AI News caught up with Janine Lloyd-Jones, director of marketing and communication at Faculty, to discuss how the benefits of AI can be unlocked while ensuring deployments remain a tool for positive change.

AI News: What are the constraints, ethical considerations, and potential for deep reinforcement learning?

Janine Lloyd-Jones: Whilst reinforcement learning can be used in video games, robotics and chatbots, the reality is that we can’t fully unlock the power of these tools as the risks are high and models like these are hard to maintain.

As AI makes more and more critical decisions about our everyday lives, it becomes even more important to know it’s operating safely. We’ve developed a first-of-its-kind explainability tool, which generates explanations quickly, incorporating causality; making it easier to improve the performance of models, because users understand how it makes decisions. This has been integral in our Early Warning System (EWS), allowing NHS staff to understand and interpret each forecast, which has increased the adoption of the tool.

It’s our view that clearer regulation is needed to ensure AI is being used safely, but this needs to be informed by what’s practical and possible to implement. We also need to ensure we don’t stifle innovation. Any regulation needs to be context-dependent. For example, when AI is used to make decisions in a medical diagnostics context, safety becomes far more important than if an AI algorithm is trying to choose which advertisement to show you. As we acquire the right tools and regulation, it’s exciting to see what complex AI like deep reinforcement learning will achieve in our industry and society.

AN: Faculty is among the companies taking admirable steps to offset its carbon emissions. How can AI play a role in combating climate change?

JL: We’re here because we believe that AI can change the world – we want to take this technology and use it to solve real, tangible, important problems.

Like many tech companies, the biggest sources of our carbon emissions are cloud computing (the tech sector has a greater carbon footprint than the aviation industry) but sustainable AI can be part of the solution. Our work includes analysing data for Arctic Basecamp and regulating pressure on the UK gas grid. We’re expanding our sustainable AI work with environmental organisations, supporting them to tackle climate change.

AN: How quickly do you think most factories will either go entirely “dark” – as in having no or very few humans working in them – or at least have a portion of them being fully autonomous? How can the workforce prepare for such changes?

JL: AI is not universal just yet, so we don’t expect we’ll see factories going entirely dark anytime soon. Most companies are using AI to automate, save time and increase productivity, but the potential of AI is huge – it will transform industries. AI can become the unconscious mind of an organisation, processing vast volumes of data quickly, and freeing humans to focus on what they’re best at and where their input is needed; humans have a far greater appreciation for nuance and context for example.

We’ve already helped clients across industries do this from cutting the backlog of cases from four years to just four weeks, developing models which detect harmful content online with a positive rate of 94% to helping large retailers ensure they are marketing to the customers most likely to purchase, increasing profits by 5%.

AN: The NHS was able to enhance its forecasting abilities thanks to its partnership with Faculty. What successes were achieved and was anything learnt from the experience that could improve future predictions?

JL: We’re really proud of our partnership with the NHS; our groundbreaking Early Warning System (EWS) was crucial in the NHS’ nationwide pandemic data strategy, forecasting spikes in Covid-19 cases and hospital admissions weeks in advance. These forecasts allowed the NHS to ensure there were enough staff, beds and vital equipment allocated for patients. There are over 1000 users of the model across the NHS.

Following the success of the tool, we are addressing new areas where AI forecasting can be used to improve service delivery and patient care in the NHS, including predicting A&E demand and winter pressures. The EWS uses our Operational Intelligence software; leveraging Bayesian hierarchical modelling to form forecasts on a national level to an individual trust level. We’ve used the same software in scenarios where demand forecasting is needed, including for consumer goods. 

AN: Faculty continues to expand rapidly and recently raised £30m that it expects to use to create 400 new jobs and accelerate its international expansion. What else is a key focus for Faculty over the coming years?

JL: We’re excited to be able to bring the power of AI to even more customers, helping them to make effective decisions with real-world impact. We are enhancing our technology offering, hiring 400 new people over the next few years and accelerating our international expansion. We are also doubling down on our AI safety research programme, so our customers have the assurance that all of our AI models are always performing safely and to the best of their ability.

AN: What will Faculty be sharing with the audience at this year’s AI Expo Global?

We’re glad to be at in-person events again, and we’re looking forward to meeting fellow exhibitors and attendees. Our focus at this year’s AI Expo will be on our Customer Intelligence software – which we are predominantly using within the consumer industries to demonstrate the impact marketing has on individual customer behaviour. Millions of marketing spend is wasted each year, being spent on the wrong people. With our technology, marketers will finally have the insight to know when and who they should be focusing their efforts on. 

We’re also sharing more about our Faculty Fellowship, our in-house L&D programme where organisations looking to expand their data science teams can hire top data scientists for six weeks before they decide to hire. This is particularly critical as the UK tech industry looks to hire and attract the top talent. We’ve already had some great companies take part in this programme from Virgin Media and Vodafone, through to leading startups like The Trade Desk and JustEat.

AN: It’s the 20th anniversary of the Faculty Fellowship in October – what’s the focus for the Fellowship over the coming years?

JL: Faculty began with the Fellowship, so it’s a really special milestone to be celebrating the 20th anniversary. With demand for data scientists at an all-time high – with over 100,000 vacancies in 2020 alone, it’s a competitive space. We expanded the programme this year to include an additional fellowship, and we’re continuously working to ensure we are attracting top talent, and making the process as easy as possible for our partner companies. 

Overstretched teams are fed up of spending their time on hiring and long interview rounds—the fellowship is designed so companies only invest 2-3 hours in total, but have an elite data scientist embedded in their team within weeks.

(Photo by Clark Tibbs on Unsplash)

Faculty will be sharing their invaluable insights during this year’s AI & Big Data Expo Global which runs from 6-7 September 2021. Faculty’s stand number is 178. Find out more about the event here.

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While the UK’s vaccine rollout is among the fastest in the world – certainly in comparison to its European peers – a series of late lockdowns and initial lack of PPE equipment has put the health service under immense pressure and left the country with one of the highest COVID-19 deaths rates per capita.

The latest lockdown was imposed after ministers were warned the NHS would collapse within a few weeks, leaving Britons unable to access care for any reason. Paramedics have already reported patients dying in ambulances queued outside of hospitals and research from King’s College London suggests around half of ICU staff are suffering from PTSD and problem drinking due to the scenes they’ve witnessed and pressure they’re under.

NHSX, the digital innovation arm of the health service, is now providing access to the National COVID-19 Chest Imaging Database (NCCID) to hospitals and universities across the country to help speed up the diagnosis of the virus and help to reduce the pressure on the health service. 

Clinicians at Addenbrooke’s Hospital in Cambridge are developing an algorithm based on the NCCID images to help inform a more accurate diagnosis of patients when they present to hospital with potential COVID-19 symptoms and have not yet had a confirmed test.

Matt Hancock, Secretary of State for Health and Social Care, said:

“The use of artificial intelligence is already beginning to transform patient care by making the NHS a more predictive, preventive, and personalised health and care service.

It is vital we always search for new ways to improve care, especially as we fight the pandemic with the recovery beyond. This excellent work is testament to how technology can help to save lives in the UK.”

The ability of clinicians to identify the virus in its earliest stages greatly increases the chance that interventions will prevent a progression to severe complications which require longer stays, extra resources, cause more suffering, and will inevitably lead to further deaths.

Carola-Bibiane Schönlieb, Professor of Applied Mathematics and head of the Cambridge Image Analysis group at the University of Cambridge, explained:

“The NCCID has been invaluable in accelerating our research and provided us with a diverse, well-curated, dataset of UK patients to use in our algorithm development.

The ability to access the data for 18 different trusts centrally has increased our efficiency and ensures we can focus most of our time on designing and implementing the algorithms for use in the clinic for the benefit of patients.

By understanding in the early stages of disease, whether a patient is likely to deteriorate, we can intervene earlier to change the course of their disease and potentially save lives as a result.”

Beyond COVID-19, the AI tools being developed are expected to help spot signs of other conditions. A ‘national AI imaging platform’ is being explored to help spot things such as cancers and heart disease in their earliest and most treatable forms.

A £140 million AI award has been established this year in collaboration with the Accelerated Access Collaborative (AAC) and National Institute for Health Research (NIHR) to speed up the deployment of AI technologies to benefit patients and staff across health and care.

Dominic Cushnan, Head of AI Imaging at NHSX, commented: “The industrial scale collaboration of the NHS, research and innovators on this project alone has demonstrated the huge potential and benefits of technology in transforming care.”

(Photo by Grooveland Designs on Unsplash)

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Dr Alex Young is a trained orthopaedic and trauma surgeon who founded Virti and set out to use emerging technologies to provide immersive training for both new healthcare professionals and experienced ones looking to hone their skills.

COVID-19 has put most in-person training on hold to minimise transmission risks. Hospitals and universities across the UK and US are now using the virtual patient as a replacement—including our fantastic local medics and surgeons at the Bristol NHS Foundation Trust.

The virtual patient uses Natural Language Processing (NLP) and ‘narrative branching’ to allow medics to roleplay lifelike clinical scenarios. Medics and trainees can interact with the virtual patient using their tablet, desktop, or even VR/AR headsets for a more immersive experience.

Dr Alex Young comments:

“We’ve been working with healthcare organisations for several years, but the pandemic has created really specific challenges that technology is helping to solve. It’s no longer safe or practicable to have 30 medics in a room with an actor, honing their clinical soft-skills. With our virtual patient technology, we’ve created an extremely realistic and repeatable experience that can provide feedback in real time. This means clinicians and students can continue to learn valuable skills.

Right now, communication with patients can be very difficult. There’s a lot of PPE involved and patients are often on their own. Having healthcare staff who are skilled in handling these situations can therefore make a huge difference to that patient’s experience.”

Some of the supported scenarios include: breaking bad news, comforting a patient in distress, and communicating effectively whilst their faces are obscured by PPE. Virti’s technology was also used at the peak of the pandemic to train NHS staff in key skills required on the front line, such as how to safely use PPE, how to navigate an unfamiliar intensive care ward, how to engage with patients and their families, and how to use a ventilator.

Tom Woollard, West Suffolk Hospital Clinical Skills and Simulation Tutor, who used the Virti platform at the peak of the COVID pandemic, comments:

“We’ve been using Virti’s technology in our intensive care unit to help train staff who have been drafted in to deal with COVID-19 demand.

The videos which we have created and uploaded are being accessed on the Virti platform by nursing staff, physiotherapists and Operational Department Practitioners (ODPs) to orient them in the new environment and reduce their anxiety.

The tech has helped us to reach a large audience and deliver formerly labour-intensive training and teaching which is now impossible with social distancing.

In the future, West Suffolk will consider applying Virti tech to other areas of hospital practice.”

The use of speech recognition, NLP, and ‘narrative branching’ provides a realistic simulation of how a patient would likely respond—providing lifelike responses in speech, body language, and mannerisms.

The AI delivers real-time feedback to the user so they can learn and improve. With upwards of 70 percent of complaints against health professionals and care providers attributable to poor communication, the virtual patient could help to deliver better care while reducing time spent handling complaints.

Virti’s groundbreaking technology has – quite rightly – been named one of TIME’s best inventions of 2020.

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Simon Stevens says the plans are part of an initiative to improve patient outcomes and deliver savings. Stevens admits some jobs are at risk, as roles such as radiographers are replaced to achieve productivity targets set in return for the NHS’ £20 billion funding boost it was given last year.

“We are seeing an artificial intelligence revolution that will be a big part of our future over the next five years, with technologies that can cut the time that patients wait for scan results and ease the burden on hardworking staff,” he said.

“We want the NHS to be first out of the blocks.”

Stevens was speaking at the Reform Health Conference, where he pledged a range of measures to incentivise the uptake of AI in the NHS.

Two million important breast cancer screenings are carried out each year. The scans currently require two clinicians to review them, making it a slow and costly process. AI has been proven to have the potential to increase efficiency in such areas and ensure potentially lifesaving treatment is started earlier.

Similarly, Stevens mentioned the use of AI at London’s Moorfields Eye Hospital which AI News has previously covered. The hospital’s tests found AI made the correct referral decision for more than 50 eye diseases with 94 percent accuracy.

Last year, the chief clinical information officer for health and care at the NHS said it’s time for technologies such as AI to be implemented.

“The [current] model of care is the 1948 model – the GP in the surgery, the community practice and district nurse in the car, the hospital with consultants and junior doctors in white coats,” said Simon Eccles. “We don’t use AI much in healthcare – and we should.”

Let’s just hope it goes better than the most recent costly adoption of AI in the NHS.

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