This article was written by Tina Woods, founder and CEO of Collider Health, a health innovation catalyst. Tina is an adviser to the National AHSN AI Programme, which is building the A! ecosystem for the NHS and launching a national survey on AI in healthcare, geared to map all organisations using or planning to use AI to deliver better health for people in the UK. Please click here to ensure your organisation is on the map and to participate in the ecosystem.

Advances in artificial intelligence (AI) and genomics will deliver more accurate diagnoses and personalised treatments, and potentially transform the NHS and self-care. Technology is now here that can gather life, health and medical data through apps, wearables, digestibles, home-based devices and sensors, and analysed using sophisticated machine algorithms to provide real-time, actionable analytics. AI could help our mental health in a number of ways through early detection, better access to care and less stigma.

Health and wellness hottest area for AI

According to market research firm CB Insights, health and wellness is the hottest area of investment in AI, with imaging and diagnostics the most active space. There have been 270 deals going to the AI health category globally since 2012, with 73% of the deals going to US start-ups, followed by the UK (9.2%) and Israel (3.7%). However, the share of non-US deals reached a five-year high in 2016 at 35%, compared to 24% or less in previous years. In 2017, over 45% of the deals went to start-ups outside the US, to countries including the UK, India, the Netherlands, Finland and Israel. See the current state of play globally in this map:

Here is just a snippet of recent news relating to the impact AI has on health:

  • According to IDC, 50% of surgeons will use computer-assisted or robotic surgery techniques to assist in planning, simulating, and performing 50% of the most complex surgeries by this year.
  • A recent study found that advanced machine learning is faster, more accurate and more efficient than board-certified echocardiographers at classifying heart anatomy shown on an ultrasound scan.
  • AI can spot signs of Alzheimer’s before your family does, as it is not always obvious when patients are in the early stages of the disease. A recent study shows that alterations in the brain can cause subtle changes in behaviour and sleep patterns years before people start experiencing confusion and memory loss.
  • The FDA recently approved Medtronic’s Guardian Connect system. Guardian Connect is a continuous glucose monitoring (CGM) tool that uses a predictive algorithm to prevent hyperglycemia and hypoglycemia in people who suffer from diabetes. The algorithm collects data from the Sugar.IQ diabetes assistant, powered by IBM Watson Health, which monitors how a patient’s blood glucose levels respond to different elements, like food intake, insulin dosages and even their daily physical routines.
  • The AliveCor KardiaBand, a sensor compatible with the Apple Watch, can detect dangerous levels of potassium in blood with 94% accuracy. Although the US Food and Drug Administration has not yet approved KardiaBand for this purpose, it’s an interesting step forward considering that, right now, the condition is usually caught using invasive blood.

While technology is here, its adoption and diffusion are taking much longer. Hopefully this will change. Consumers are already buying digital health products and services, and the government is pushing hard to equip Britain as a global leader in technology in a post-Brexit world.

AI and citizen data

Increasing scrutiny on the data practices of commercial organisations has resulted from the recent Cambridge Analytica–Facebook situation.  With the General Data Protection Regulation (GDPR) coming into force on 25 May, Europe is well-positioned to lead a very different kind of data revolution and momentum is growing for a new way of leveraging data for wider societal good, recognising the limitations of global capitalism, the rise of China and the continued strength of the global tech giants.

The Nuffield Foundation has just announced the £5m Ada Lovelace Institute to “examine profound ethical, and social issues arising from the use of data, algorithms, and artificial intelligence, and to ensure they are harnessed for social well-being”.  A recent  article by Hetan Shah (Royal Statistical Society) argues that technology giants should take lessons from the Human Genome Project and be data stewards, not data owners.

A report, Data and the future of health and care, from a recent Round Table held by the Future Health Collective made a number of recommendations including the promotion of data philanthropy and the formation of a trusted data vehicle to create the foundations of a template for citizens to share their data for research and charitable purposes, an option that does not exist today in any scalable manner. The creation of trusted data vehicles or data trusts would drive a new generation of business models and also nurture the SME sector (critical in a post-Brexit world) by giving start-ups the data they desperately need to develop their businesses.

Hugh Harvey, chief medical officer for Kheiron Medical, says in his recent article that the UK could be a world leader in radiology AI, arguing for the creation of British Radiology Artificial Intelligence Network  (BRAIN). The idea is to create access to anonymised NHS medical imaging data through a central data science hub governed under the remit of the NHS, with profits from successful research fed back into the national health and research system. Software created could then be exported, creating global revenue streams and cementing the UK as the world leader in this field.

Government support for AI

The government and the AI sector have agreed a Sector Deal to boost the UK’s global position as a leader in developing AI technologies and the Industrial Strategy published in November 2017 announced the AI and Data-Driven Economy Grand Challenge, geared to anchor the UK as the go-to destination for AI innovation and investment. The Sector Deal builds on the review by Professor Dame Wendy Hall and Jérôme Pesenti, Growing the artificial intelligence industry in the UK, which involved an extensive range of business leaders, academics and research councils.

The deal recognises the critical importance of data availability, and its responsible use, to businesses at the forefront of the development of AI applications. The government and industry will work together to establish data trusts, an innovative approach to stimulating fair, safe and equitable data sharing between parties. To be global leaders in the application of AI, companies must attract the talent they need, and the government is committed to working together to build and maintain the best AI workforce in Europe, focusing on postgraduate-level skills and above.

In support of the Grand Challenge on data and AI, a new Centre for Data Ethics and Innovation is being established to enable and ensure safe, ethical and groundbreaking innovation in AI and data-driven technologies. The centre will work with the government, regulators and industry leaders, as well as across sectors and applications, to ensure that our regulatory regime fully supports – and removes barriers to – the ethical and innovative use of data and AI. This will lay the foundations for AI adoption, which could benefit households across the UK by up to £2,300 per year by 2030 and ensure that the positive impact of these technologies on the UK economy and society can be maximised.

The AI Select Committee has just launched a report, AI in the UK: Ready, willing and able?, to encourage investment in AI and create a legislative environment that builds on the framework established by GDPR. The report says the UK is in a strong position to be a world leader in the development of AI, but it must put ethics at the centre of AI’s development for maximum economic boost and benefit to society.

The Select Committee argues that data held by the NHS could be considered a unique source of value for the nation; it should not be shared lightly, but when it is, it should be done in a manner which allows for that value to be recouped. They recommend that a framework for the sharing of NHS data should be prepared and published by the end of 2018 by NHS England (specifically NHS Digital) and the National Data Guardian for Health and Care, with the support of the Information Commissioner’s Office, and the clinicians and NHS Trusts that already have experience of such arrangements (such as the Royal Free London and Moorfields Eye Hospital NHS Foundation Trusts), as well as the Caldicott Guardians.

This framework should clearly set out the considerations needed when sharing patient data in an appropriately anonymised form, the precautions needed when doing so, and an awareness of the value of that data and how it is used. It must also take into account the need to ensure SME access to NHS data, and ensure that patients are made aware of the use of their data and their options.

The Committee recommends that wherever possible and appropriate, and with regard to its potential commercial value, publicly held data be made available to AI researchers and developers. While open data cannot be the last word in making data more widely available and usable, and can often be too blunt an instrument for facilitating the sharing of more sensitive or valuable data, legal and technical mechanisms for strengthening personal control over data, and preserving privacy, will become increasingly important as AI becomes more widespread through society. Mechanisms for enabling individual data portability, such as the Open Banking initiative, and data sharing concepts such as data trusts, will spur the creation of other innovative and context-appropriate tools, eventually forming a broad spectrum of options between total data openness and total data privacy.

Finally, the Select Committee recommends that the Centre for Data Ethics and Innovation investigate the Open Banking model and other data portability initiatives, as a matter of urgency, with a view to establishing similar standardised frameworks for the secure sharing of personal data beyond finance. They should also work to create, and incentivise the creation of, alternative tools and frameworks for data sharing, control and privacy for use in a wide variety of situations and contexts.

These recommendations support those of the Life Sciences Industrial Strategy (published before the Industrial Strategy in November) to create regional digital innovation hubs that support the use of data for research purposes within the legal framework, and meet the strict parameters for sharing data and the security standards set out by the National Data Guardian. These hubs will create controlled environments for real-world clinical studies, the application of novel clinical trial methodology, and the comprehensive evaluation of new innovations so that patients can benefit from scientific breakthroughs much faster. Major companies including Philips, Roche Diagnostics and Leica are already in discussion with the government and the NHS to develop a trail-blazing digital pathology programme using artificial intelligence.

Hottest UK AI health start-ups

Hot UK start-ups to watch include (see the recent report, The Promise of HealthTech, for a comprehensive listing):

  • Kheiron Medical is a medical imaging company that has developed a computer-aided radiology diagnostics tool powered by machine learning. This will allow radiology departments, imaging centres and hospitals to improve the efficiency, consistency and accuracy of radiology reporting and tracking.
  • Ultromics is a cardiovascular diagnostics company that has combined machine learning and one of the world’s largest cardiac imaging datasets to automatically diagnose heart disease from echocardiograms with a 90% accuracy rate.
  • uses deep-learning technologies to make medical imaging diagnostics more accurate and efficient, and was recently awarded FDA approval for its LVO Stroke Platform, heralding the start of intelligent stroke care.
  • Cambridge Bio-Augmentation Systems is creating neural interfaces for the next generation of AI-powered healthcare.
  • Brainomix is a medical imaging company using AI for the fast diagnosis and treatment of stroke victims, and recently raised £7m in funding.