Artificial Intelligence (AI) holds enormous potential for the future of healthcare. It can reduce the burden on healthcare systems by performing tasks that can be converted into an algorithm, many of which are in areas of greatest pressure, like radiography and pathology. It could improve patient outcomes, and increase productivity across systems, freeing up clinicians’ time so they can focus on the parts of the job where they add the most value.
That’s if we get AI right.
Ethics first
“It is now generally accepted by the medical community that AI can be a useful companion to enable precision medicine and a higher quality of care,” says Jan Beger, applications director at GE Healthcare Digital, Europe. “The regulation of AI is key. We strongly support the European Commission’s initiative to build a framework for trustworthy AI, that is lawful, ethical and robust. Active collaboration is needed between academia, society and industry, in which we’re happy to fully participate.”
Tamás Békási of EIT Health InnoStars is responsible for early-stage start-ups that develop AI in healthcare, among others.
“The first thing we need to keep our eyes on are ethics,” he tells Emerging Europe. “From the protection of our personal data to the limits of automated medical decision making, there are many fields where the progress of innovation needs to take careful steps.”
An innovation gold rush
Mr Békási believes that there is both “hidden innovation potential” and “unexplored opportunities” in Central, Eastern and Southern Europe. “Investors from Europe, the US, Asia and Israel, as well as other ecosystem players are realising this more and more. We can therefore talk about an innovation gold rush in this region.”
Finding and polishing that innovative gold is something that EIT Health is increasingly adept at doing. Backed by the European Union, EIT Health’s role is to build a network that enables the development of healthcare innovation for the future so that European citizens can live longer and healthier lives. It is a network that predates Covid-19, but one which has proven to be agile enough to pivot in order to effectively fight the pandemic.
One of the AI start-ups that has benefitted from its membership of the EIT Health network is Poland’s Brainscan, which uses machine learning to improve the efficiency of brain CT scan interpretation by giving radiologists an AI-based decision support system to lessen misdiagnosis.
“Being a part of the EIT Health Headstart programme was a truly remarkable step forward,” says Brainscan’s COO, Dariusz Wiśniewski.
“The funding enabled us to develop an API for integrations, which perfectly aligns with our mission to integrate into the diagnostic sphere as seamlessly as possible. Our system lowers the chances of misdiagnosis and speeds up the radiology interpretation flow, saving lives and creating a more sustainable health ecosystem by reducing unnecessary procedures. The relationships we established via the programme allowed us to start conversations with the majority of CT scanner manufacturers, such as GE, Philips, and Siemens Healthineers – as a result of which we have the potential to cover nearly 100 per cent of the European market.”
Another AI-orientated team is XVision, a Romanian start-up changing modern radiology.
“The idea of the product comes from our team’s belief that AI can be a tool that is useful to humanity, and that medical imaging is a great place for this idea to be put in practice,” says CEO Ştefan Iarca. “AI algorithms can handle images extremely well, but there’s a genuine problem with a worldwide lack of radiologists compared to the growing number of medical images generated. With our know-how in machine learning, we decided to take a shot at trying to solve this problem.”
Iarca is adamant that EIT Health was paramount in the firm’s progress.
“Not only did we get to discuss with extremely qualified mentors who know the specifics of the healthcare domain, but we also had access to a large network of stakeholders and potential clients,” he says. “I believe that the advice we got helped us shape our company and pivot at the right time and in the right aspects, and the network that we had access to allowed us to connect with the people that we needed, which strongly accelerated our growth.”
The next generation
A recent report from EIT Health and McKinsey and Company has exposed an urgent need to attract, educate and train a generation of data-literate healthcare professionals, whilst up-skilling the current workforce if we are to fully realise the transformative potential of AI. The report found that basic digital skills, biomedical and data science, data analysis, and the fundamentals of genomics will be critical, if AI and machine learning is to penetrate healthcare services.
The incentives for healthcare systems to embrace these changes are clear. The WHO estimates that by 2030 the world will be short of 9.9 million doctors, nurses and midwives, which adds further urgency to address the challenge of already overburdened health systems. Supporting the widespread adoption and scaling of AI could help alleviate resource capacity shortfalls both now and in the future, for example, by streamlining or even eliminating administrative tasks which can occupy anything between 20 and 80 per cent of a healthcare professional’s time. At present, diagnostics is the main application of AI within healthcare. However, over the next 5-10 years, healthcare professionals expect clinical decision making to top the list of applications, according to the report.
Besides upskilling, better involvement of healthcare professionals in the early stages of AI development was also identified as a key need. Currently, 44 per cent of those surveyed, chosen for their interest in healthcare innovation and AI, had never been involved in the development or deployment of an AI solution.
Global players have already started to educate the talent pool in the field of AI. GE Healthcare, the KTH Royal Institute of Technology Stockholm and Barcelona-based LEITAT Technological Centre, organise a free online AI training programme designed to introduce participants to the basics of Artificial Intelligence, unveil and discover its challenges and build a community of curious and forward-thinking individuals.
“Basic digital skills, biomedical and data science, data analysis, and the fundamentals of genomics will be critical, if AI and machine learning is to penetrate healthcare services,” says Jorge Fernández García, director of innovation at EIT Health. “These subjects are rarely taught alongside traditional clinical sciences systematically. And so, through no fault of their own, today’s healthcare workforce is simply not yet equipped for the adoption of AI.”
Called HelloAIRIS, the joint programme is an effort to address this challenge, and to bring AI technology closer to the next generation.
“We started the HelloAI summer school for European university students about the use of AI in healthcare two years ago,” says Peter Bencsik, consortium research leader at GE Healthcare. “We aim to provide valuable content for participants from diverse backgrounds. Medical, engineering and economics students can all find interesting topics in this field and will work together to solve unmet needs in the future.
“We cover the fundamentals and the practical implementations, too. Due to Covid-19, this year we will hold online lectures, but we will organise live sessions where participants can directly engage with the experts, ask questions, validate ideas. We will miss the face to face interaction of previous years but let’s look at the positive side: the opportunity will be available to a much wider audience. As one of our alumni rightly put it: ‘AI in healthcare: here you can actually learn it, instead of just talking about it.’”
Thought leadership
AI will be one of main topics this autumn at EIT Health’s Think Tank – its thought-leadership forum.
“Being at the forefront of healthcare innovation in Europe, we are seeing an increasing number of tangible, impactful and exciting AI solutions created. However, we must couple the generation of new technology that can relieve some of the pressure on healthcare services, with the ability for it to be integrated into care delivery. Now is the time for us to address the gaps, so that Europe does not fall behind in the application of AI,” concludes Jorge Fernández García.
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