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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Health secretary Matt Hancock has championed GP at Hand since 2017. The digital service has come into question for providing unsafe recommendations, and for taking money away from surgeries already struggling with cuts.

The service has operated through the Hammersmith and Fulham Clinical Commissioning Group (CCG) across London. Due to the popularity of the app, the CCG has ended up with a £21.6m funding gap while it plans £10m of additional cuts.

According to the CCG, it’s working on a “solution to the financial impact” of GP at Hand and expects reimbursement from NHS England. The CCG promises that patients in Hammersmith and Fulham will “not be disadvantaged” by the funding gap.

The Hammersmith and Fulham CCG’s total deficit swelled to £37m this year. Cuts are planned in a wide range of areas including overnight urgent care centres, out of hours GP services, radiology, cardiology, gynaecology, mental health services, dementia support, rehabilitation, and more.

Babylon said: “We fully expect Babylon GP at Hand to reduce the costs on the overall NHS,” adding the NHS’s financial structure is “not designed to meet the needs of people who choose digital-first care”.

GP at Hand has appealed primarily to the younger generation who are used to digital services. Babylon Health has, in the past, been criticised for picking healthier patients and leaving more complicated cases to surgeries. Due to each surgery being funded on a per patient basis, this means GPs are being left with less overall funding to cover patients which use their services more.

Ipsos Mori was commissioned by the NHS last year to assess the impact of Babylon Health’s partnership with the NHS. On Thursday, the research group published its findings and said there were “questions about the financial impact of the service on the wider health system”.

AI-powered healthcare solutions will one day fulfil their exciting promise, but rushing to market only risks patients’ wellbeing.

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In the keynote session, titled ‘What is the true adoption of AI’, Hogan provided real-world examples of how the technology is being used and enabled by Nvidia’s GPUs. But first, he highlighted the momentum we’re seeing in AI.

“Many governments have announced investments in AI and how they’re going to position themselves,” comments Hogan. “Countries around the world are starting to invest in very large infrastructures.”

The world’s most powerful supercomputers are powered by Nvidia GPUs. ORNL Summit, the current fastest, uses an incredible 27,648 GPUs to deliver over 144 petaflops of performance. Vast amounts of computational power is needed for AI which puts Nvidia in a great position to capitalise.

“The compute demands of AI are huge and beyond what anybody has seen within a standard enterprise environment before,” says Hogan. “You cannot train a neural network on a standard CPU cluster.”

Nvidia started off by creating graphics cards for gaming. While that’s still a big part of what the company does, Hogan says the company pivoted towards AI back in 2012.

A great deal of the presentation was spent on autonomous vehicles, which is unsurprising given the demand and Nvidia’s expertise in the field. Hogan highlights that you simply cannot train driverless cars using CPUs and provided a comparison in cost, size, and power consumption.

“A new type of computing is starting to evolve based around GPU architecture called ‘dense computing’ – the ability to build systems that are highly-powerful, huge amounts of computational scale, but actually contained within a very small configuration,” explains Hogan.

Autonomous car manufacturers need to train petabytes of data per day, reiterate their models, and deploy them again in order to get those vehicles to market.

Nvidia has a machine called the DGX-2 which delivers two petaflops of performance. “That is one server that’s equivalent to 800 traditional servers in one box.”

Nvidia has a total of 370 autonomous vehicles which Hogan says covers most of the world’s automotive brands. Many of these are investing heavily and rushing to deliver at least ‘Level 2’ driverless cars in the 2020-21 timeframe.

“We have a fleet of autonomous cars,” says Hogan. “It’s not our intention to compete with Uber, Daimler or BMW, but the best way of us helping our customers enable that is by trying it ourselves.”

“All the work our customers do we’ve also done ourselves so we understand the challenges and what it takes to do this.”

Real-world impact

Hogan notes how AI is a “horizontal capability that sits across organisations” and is “an enabler for many, many things”. It’s certainly a challenge to come up with examples of industries that cannot be improved to some degree through AI.

Following autonomous cars, Nvidia sees the next mass scaling of AI happening in healthcare (which our dear readers already know, of course.)

Hogan provides the natural example of the UK’s National Health Service (NHS) which has vast amounts of patient data. Bringing this data together and having an AI make sense of it can unlock valuable information to improve healthcare.

AIs which can make sense of medical imaging on a par with, or even better, than some doctors are starting to become available. However, they are still 2D images that are alien to most people.

Hogan showed how AI is able to turn 2D imagery into 3D models of the organs which are easier to understand. In the GIF below, we see a radiograph of a heart being turned into a 3D model:

We’ve also heard about how AI is helping with the field of genomics, assisting in finding cures for human diseases. Nvidia GPUs are used for Oxford Nanopore’s MinIT handheld which enables DNA sequencing of things such as plants to be conducted in-the-field.

In a blog post last year, Nvidia explained how MinIT uses AI for basecalling:

“Nanopore sequencing measures tiny ionic currents that pass through nanoscale holes called nanopores. It detects signal changes when DNA passes through these holes. This captured signal produces raw data that requires signal processing to determine the order of DNA bases – known as the ‘sequence.’ This is called basecalling.

This analysis problem is a perfect match for AI, specifically recurrent neural networks. Compared with previous methods, RNNs allow for more accuracy in time-series data, which Oxford Nanopore’s sequencers are known for.”

Hogan notes how, in many respects, eCommerce paved the way for AI. Data collected for things such as advertising helps to train neural networks. In addition, eCommerce firms have consistently aimed to improve and optimise their algorithms for things such as recommendations to attract customers.

“All that data, all that Facebook information that we’ve created, has enabled us to train networks,” notes Hogan.

Brick-and-mortar retailers are also being improved by AI. Hogan gives the example of Walmart which is using AI to improve their demand forecasting and keep supply chains running smoothly.

In real-time, Walmart is able to see where potential supply challenges are and take action to avoid or minimise. The company is even able to see where weather conditions may cause issues.

Hogan says this has saved Walmart tens of billions of dollars. “This is just one example of how AI is making an impact today not just on the bottom line but also the overall performance of the business”.

Accenture is now detecting around 200 million cyber threats per day, claims Hogan. He notes how protecting against such a vast number of evolving threats is simply not possible without AI.

“It’s impossible to address that, look at it, prioritise it, and action it in any other way than applying AI,” comments Hogan. “AI is based around patterns – things that are different – and when to act and when not to.”

While often we hear about what AI could one day be used for, Hogan’s presentation was a fascinating insight into how Nvidia is seeing it making an impact today or in the not-so-distant future.

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NHS doctors are overburdened; a problem only getting worse from a growing and ageing population, and not enough funding.

The report was led by US academic Eric Topol and calls for a reskilling of NHS staff to harness new digital skills. AI and robotics can reduce the burden on healthcare professionals, but only if they’re utilised effectively.

Doctors will not be replaced by robots but instead will have their abilities “enhanced” to improve care. Around 90 percent of all NHS jobs are predicted to require digital skills within the next 20 years.

The use of virtual assistants such as those offered by Apple, Google, and Amazon are expected to be among the closest innovations to being ready.

Assistants can help with checking whether symptoms require urgent care, a GP appointment, or whether a doctor needs to be seen at all. This would help prevent the misuse of A&E by people with trivial ailments or the booking of GP appointments for otherwise healthy adults with things such as a common cold.

Virtual assistants could also be used to book and remind of appointments. This would help to reduce the number of unattended appointments that someone else could have needed.

Yet another concept is the use of a ‘mental health triage bot’ that engages in conversations while analysing text and voice for suicidal ideas and emotion. This could help reduce the ~6000 suicides per year.

The main concern preventing uptake is the potential for errors, which in healthcare could be fatal.

AI News previously reported on the findings of NHS consultant ‘Dr Murphy’ who reached out to us after using ‘GP at Hand’ from Babylon Health, an AI-powered service promoted by health secretary Matt Hancock.

Dr Murphy has since posted many flawed experiences with the service, but one example of a “48yr old obese 30/day male smoker develop[ing] sudden onset central chest pain & sweating” suggested booking a GP appointment. Anyone with common sense would say call 999 urgently.

That example could have meant life or death and shows, while such a system could one day provide huge benefits, it must undergo rigorous testing.

Commenting on the report, Hancock said:

Our health service is on the cusp of a technology revolution and our brilliant staff will be in the driving seat when it happens.

Technology must be there to enhance and support clinicians. It has the potential to make working lives easier for dedicated NHS staff and free them up to use their medical expertise and do what they do best: care for patients.”

In the NHS report, it’s claimed the use of virtual assistants could save 5.7 million hours of GP’s time across England per year.

Further AI use cases include speeding up the interpretation of scans; improving accuracy while enabling treatments to begin sooner. We’ve created a dedicated ‘healthcare’ category on AI News highlighting the incredible advances in this area.

When it comes to robotics, their assistance in surgery could be expanded in addition to being used for simple tasks which are important but time-consuming such as dispensing medicines.

Other emerging technologies such as VR also present exciting opportunities. Virtual reality could help with pain reduction and treating mental conditions such as post-traumatic stress, anxiety, and phobias.

The report’s authors conclude: “Our review of the evidence leads us to suggest that these technologies will not replace healthcare professionals, but will enhance them … giving them more time to care for patients.”

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Speaking to The Guardian in 2016, DeepMind CEO Demis Hassabis said:

“We are able to literally get the best scientists from each country each year. So we’ll have, say, the person that won the Physics Olympiad in Poland, the person who got the top maths PhD of the year in France.

We’ve got more ideas than we’ve got researchers, but at the same time, there are more great people coming to our door than we can take on.”

In recent months, however, that renowned talent has started leaking out. Over the past 24 hours alone, two leading DeepMinders have announced they’re leaving the company.

Edward Grefenstette, a leading research scientist, announced he’s joining Facebook’s AI facility just down the road from DeepMind’s headquarters in London. Grefenstette co-founded Dark Blue Labs, a deep learning startup that DeepMind acquired in 2014.

Jack Kelly, a research engineer, has decided to leave DeepMind and launch a non-profit lab focused on fixing climate change. Kelly undertook the Computer Science MSc at Imperial College London with the explicit aim of using AI to mitigate climate change.

Such high-profile employees announcing their departure from a once 100 percent staff retention firm, within hours of each other, leads to wonder about deeper problems.

Outside the company, there are concerns about Google’s acquisition of DeepMind. These were reignited at the end of last year when Google absorbed DeepMind Health’s Streams app.

DeepMind Health was already controversial. In 2017, the UK government ruled the company had gained inappropriate access to medical data from 1.6 million patients when developing Streams.

Mustafa Suleyman, Head of Applied AI at DeepMind, wrote in a blog post:

“DeepMind operates autonomously from Google, and we’ve been clear from the outset that at no stage will patient data ever be linked or associated with Google accounts, products or services.”

Critics say this promise was broken when Streams was grabbed by Google.

The situation is sure to make potential future partners question whether to share data with DeepMind. Healthcare is one area set to benefit most from AI, yet it’s one that DeepMind could now struggle to find allies for.

Some of these concerns are sure to be held inside the company’s walls, but to what extent – and whether they’re resignation worthy – is unclear.

A pattern that has emerged from speaking to DeepMind employees is the mutual respect shared between researchers. At least one former employee maintains that DeepMind remains a great place to work.

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Patients will benefit from the use of AI to diagnose problems earlier, greatly increasing the chances of successful treatment.

Health Secretary Matt Hancock said:

“Artificial intelligence will play a crucial role in the future of the NHS – and we need to embrace it by introducing systems which can speed up diagnoses, improve patient outcomes, make every pound go further, and give clinicians more time with their patients.

As part of our long-term plan, we will transform the NHS into an ecosystem of enterprise and innovation that allows technology to flourish and evolve.”

The new centres are based in Leeds, Glasgow, Oxford, Coventry, and London but will share their expertise with partners across the UK. Findings and breakthroughs will lead to better treatment decisions across the NHS.

Here is what each centre will focus on:

• London Medical Imaging and Artificial Intelligence Centre for Value-Based Healthcare will use artificial intelligence in medical imaging and related clinical data for faster and earlier diagnosis and automating expensive and time-consuming manual reporting
• Glasgow’s I-CAIRD (Industrial Centre for AI Research in Digital Diagnostics) will bring together clinicians, health planners, and industry to work with innovative SMEs to answer clinical questions, and solve healthcare challenges more quickly and efficiently
• NCIMI (National Consortium of Intelligent Medical Imaging) in Oxford will consider the role clinical imaging plays in the delivery of more personalised care and earlier diagnosis to support disease prevention and treatment
• The Northern Pathology Imaging Collaborative (NPIC) located in Leeds will boost the city’s reputation in digital pathology research further by creating a world-leading centre linking up 9 industry partners, 8 universities and 9 NHS trusts
• Based in Coventry, the Pathology image data Lake for Analytics, Knowledge and Education (PathLAKE) will use NHS pathology data to drive economic growth in health-related AI

AI is a major part of the UK government’s so-called Industrial Strategy. Over four years, £4.7 billion will be invested to address the opportunities and challenges of the future.

Business Secretary Greg Clark said:

“AI has the potential to revolutionise healthcare and improve lives for the better. That’s why our modern Industrial Strategy puts pioneering technologies at the heart of our plans to build a Britain fit for the future.

The innovation at these new centres will help diagnose disease earlier to give people more options when it comes to their treatment and make reporting more efficient, freeing up time for our much-admired NHS staff time to spend on direct patient care.”

The current plan is to have the new centres operational during 2019.

 AI & >.

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Cancer has a higher successful treatment rate the earlier it’s diagnosed. The later the diagnosis, the greater the risk of death or long-term debilitating effects.

In her speech, Mrs May will say:

“Late diagnosis of otherwise treatable illnesses is one of the biggest causes of avoidable deaths.

The development of smart technologies to analyse great quantities of data quickly, and with a higher degree of accuracy than is possible by human beings, opens up a whole new field of medical research and gives us a new weapon in our armoury in the fight against disease.

Achieving this mission will not only save thousands of lives, it will incubate a whole new industry around AI-in-healthcare. It will create high-skilled science jobs across the country – drawing on existing centres of excellence in places like Edinburgh, Oxford, and Leeds – and help to grow new ones.”

At least 50,000 people a year suffering from lung, prostate, ovarian, or bowel cancer will be diagnosed earlier due to AI, May will claim.

To achieve this goal, researchers will require access to large amounts of medical records to cross-reference patients’ lifestyles, genetics, and prior conditions to highlight when individuals are most at risk.

The UK’s National Health Service (NHS) has vast amounts of data. Every time a patient visits a service anywhere in the country, a record is made.

A patient’s medical record can include:

• • treatments received or ongoing

• • information about allergies

• • current medication(s)

• • any reactions to medications in the past

• • any known long-term conditions, such as diabetes or asthma

• • medical test results such as blood tests, allergy tests, and other screenings

• • any clinically relevant lifestyle information, such as smoking, alcohol or weight

• • personal data, such as age, name, and address

• • consultation notes, which a doctor takes during an appointment

• • hospital admission records, including the reason

• • hospital discharge records, which will include the results of treatment and whether any follow-up appointments or care are required

• • X-rays

• photographs and image slides, such as MRI scans or CT scans

How this data is shared and used to improve medical care remains a controversial topic. For example, the NHS’ sharing of data with Google-owned DeepMind has often come under scrutiny.

An independent panel last year found the deal between DeepMind and the Royal Free NHS Foundation Trust to develop an app for diagnosing kidney disease was ‘illegal’ and did not do enough to safeguard patient data.

Theresa May’s party, the Conservatives, have also faced widespread criticism over under-funding and privatisation of the NHS — leading to increased staff pressure and longer waiting times for patients.

Two-thirds of NHS trusts reported having at least one cancer patient waiting more than six months last year, while almost seven in 10 (69%) trusts said they had a worse longest wait than in 2010. One cancer patient waited 541 days for treatment.

If employed correctly, the automation offered by AI has the potential to greatly reduce staff pressure and improve patient care.

“Earlier detection and diagnosis could fundamentally transform outcomes for people with cancer, as well as saving the NHS money,” comments Sir Harpal Kumar, CEO of Cancer Research. “Advances in detection technologies depend on the intelligent use of data and have the potential to save hundreds of thousands of lives every year.”

“We need to ensure we have the right infrastructure, embedded in our health system, to make this possible.”

What are your thoughts on the use of AI in healthcare?

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The UK’s health service continues to be underfunded despite an increasing number of warnings from doctors and staff. Patients lined up in corridors are now a sight often seen in hospitals up and down the country.

Reform highlights 16 areas where AI can be used to improve efficiency in the NHS. Without adequate funding in sight, the recommendations aim to ensure the health service remains available to as many people as possible.

Use of patient data in healthcare is often plagued with controversy due to how sensitive the information could be. For example, the UK’s Information Commission (ICO) ruled the Royal Free NHS Foundation Trust did not do enough to protect the privacy of patients when it shared data with Google-owned AI specialists DeepMind for its research.

Cases like this damage advancements in the field. Reform says that, despite the hype around AI in healthcare, examples of it being implemented and deployed in the NHS are sparse.

One area where AI could be utilised, according to the report, is to predict individuals or groups who are particularly at risk of ailments. This will help to ensure treatment or prevention methods are targeted more effectively.

All data must be collected in the right format and accessible for advancing research, however it must also be secured adequately and ensure privacy. The report highlights the need for the NHS to become more digital to facilitate this as the service is still too reliant on paper files.

Parliamentary Science and Technology Committee chair Norman Lamb said:

“We are on the brink of a major transformation in the way we diagnose, treat, and even prevent ill health. Whether it is wearable devices, AI surgical robots, or AI algorithms that can detect certain conditions with unprecedented speed and accuracy, these advances have the potential to propel the health and social care system into the 21st century – improving care both in the hospital and at home, and making much more efficient use of resources.

There is still more to do for AI to win the hearts of all healthcare professionals, and these are just some of the issues that will occupy policymakers in the years ahead.

Infrastructure for collecting, sharing and accessing data need to be improved. Resolving the ethical questions surrounding AI in healthcare settings will be crucial, including setting the right regulatory framework.”

The full report is available for download here.

What are your thoughts on the use of AI in the NHS?

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GP at Hand aims to reduce the burden on GPs while also cutting the waiting time it takes for a patient to see a doctor from the current average of two weeks, to just a matter of minutes.

Dr Howard Freeman MBE, senior GP said: “GP at Hand is a window into what the NHS of the future will look like. When innovative NHS GPs embrace babylon technology to make life better for their patients, the sky is the limit.”

A patient gets started by moving their medical records over to the digital-first service just as they would moving practice. Patients can determine using an AI in the app if their symptoms require further attention. If required, the app puts the patient in a video chat with a GP as soon as one is available. Any prescriptions can be sent automatically to a pharmacy of the patient’s choice.  If deemed necessary, the patient can be booked in to be examined at a practice.

There are multiple benefits to this approach:

Accessibility. People with limited mobility, for example, may have other ailments which don’t require visiting a practice — but doing so today can be difficult.

Convenience. Growing waiting times means it can take weeks to get a normal appointment, and then journeying to — and sitting around in a practice waiting for your turn while feeling unwell  — is not ideal.

Rather than wake up early to beg a poor receptionist dealing with multiple other calls for an appointment, the ability to request one from your mobile device and get on with your day until the GP is ready would be preferable to many patients.

Further down the line, more GPs could even work digitally from home while taking shifts on who staffs the now less burdened practices.

Hygiene. While steps are taken to improve hygiene, anywhere there’s a lot of people sick carries risk. Doctors can end up unwell themselves and patients in the waiting room could end up leaving with illnesses they didn’t come in with.

Need. By employing AI, the many patients who unnecessarily take up precious GP time can be filtered out while ensuring GPs are available to people who need them.

Record. Speaking from experience, some of us can be forgetful. GP at Hand allows patients to privately go back over recordings of their calls with GPs if they forget any crucial advice to remind them.

Privacy. Patients can speak to a doctor from the privacy of their own home which may comfort some concerned they may run into a friend or neighbour at their local practice.

Currently, the service is only available in London, but there are plans to roll it out nationwide. When patients do need to see a GP in person, clinics are located at convenient locations for commuters and workers including Canary Wharf, Victoria, Liverpool Street, and Euston.

Patients appear to be happy with the service, based on its trial in Fulham. 90 percent gave it a 5-star rating, and 96 percent when also including 4-star ratings. This is much higher satisfaction than with current overburdened practices.

“I know just how difficult times are for GPs these days and how busy they are. GP at Hand, in addition to being very convenient for patients, can help the service given the recruitment crisis we know is facing us,” comments Dame Barbara Hakin, formerly a GP and National Director in NHS England. “This technology can take more of the strain and ensure the best information and insight is available ahead of consultations which will then relieve some of the pressure on hard pressed clinicians.”

In just a few weeks, 3,000 people have become members of the new service, with over 10,000 more registering their interest to join as the service rolls out.

Are you glad to see AI being used to modernise healthcare?

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