An ambitious target to help people live longer
Amsterdam is set to celebrate its 750th birthday in 2025. For this special occasion, the Amsterdam Economic Board (AEB), which aims to strengthen collaboration between businesses, knowledge institutes and government organisations to improve the Amsterdam Area, has set itself an ambitious goal: extending the average lifespan of the citizens living in the Amsterdam Area by two years. Big data and AI are set to play a key part in reaching this goal.
Making people healthy with AI
Jeroen Maas, challenge lead health for AEB, says that AI will revolutionise healthcare in the coming years.
“The amount of data, as well as the availability and reliability of data, have greatly improved over the past years”, Maas, who has an extensive background in academia, healthcare and entrepreneurship, explains. “You could just see things come together over time, like a wave. Businesses were starting to use it for their own practices; there was more funding for research; it all gained traction.”
Identifying this trend, three years ago the AEB started bringing different parties in government, business and universities. The aim was to connect policy making, market knowledge and expertise in both healthcare and AI, and so help speed up the process of creating practical applications using AI within a medical setting.
“Of course,” Maas says, “medical science has always been active in what you could describe as ‘manual intelligence’, using large data groups to gain insights into a specific study. If we combine sources of data and if we can implement machine learning, we’re looking at speeding up medical processes by years. That’s a massive benefit.” Maas says that the AEB’s work connecting different stakeholders in AI is already resulting in a proliferation of new businesses, work groups and projects in the Amsterdam Area.
Read about Dutch startup Pacmed's AI work in healthcare.
Prevention: even better than the cure
Maas particularly sees an opportunity for solutions involving machine learning when it comes to the prevention of bad health, rather than as a cure to fix it. “There’s a certain point where people go to the doctor”, Maas notes. “But that’s usually only when symptoms become really severe. What we’re particularly interested in, is that 'twilight zone' before people go to the doctor. There is so much information surrounding that that we are currently not using.”
This data from the ‘twilight zone’ didn’t use to exist: doctors generally only had data from the point we step through their door. But now that we are all carrying phones, we’re continuously creating data: in sickness, but also in health. From searching for symptoms on Google to our calendar appointments and even when not using our phone at all: our devices act as a comprehensive diary of our health.
“There’s great value in the data we generate just by using our phones”, says Maas. “One way of trying to improve healthcare by using AI is to look for patterns in that data. Those patterns can be indications of areas to improve. For example, AI can really help with the speed and accuracy of a diagnosis. It can also reduce long waiting lists at clinics and at hospitals, speed up customised care, help to prescribe the right amount of medication at the right time and even predict outbreaks of disease.”
Amsterdam: more than the sum of parts
It’s not just the right time to work on solutions in AI, it’s also the right place, as the Amsterdam Area already has an advantage over other regions. “Machine learning is something we are really good at here in Amsterdam”, Maas explains. “There are a lot of moving parts that are coming together in the area: universities, university hospitals and other medical facilities all focusing on AI, as well as innovative, solution-driven businesses. Hubs like the Amsterdam Science Park are a shining example of how all these elements can come together in one physical space.”
Maas also mentions the region’s strong track record in data collection, research and ethics. “It’s about truly thinking through an entire process, anticipating any issues and questions. When that is done correctly, you end up with intelligent, applicable and actionable outcomes. Ultimately, the use of data is going to strengthen the implementation of fact-based policy making, which is to the advantage of all of the Amsterdam Area’s citizens.”
The challenges for using AI in healthcare
Of course, there’s still a lot of work to be done to meet the goal of helping citizens to live longer, healthier lives. “AI is a buzz term, but if you look at any industry, it’s as important to figure out the infrastructure around the solutions”, Maas notes.
“First of all, data does not necessarily contain valuable information. It’s very possible that we could find patterns in data that confirm existing knowledge. For example, take prostate cancer: if a man lives long enough, at some point he will probably get prostate cancer. The data that we have points to this as well, but it is what healthcare professionals have already known for a long time.” The example emphasises the need for parties to share their knowledge to ensure that results and solutions are actually needed.
Next to this, there is a need for people to willingly share their data to benefit public health. Awareness and consent are obviously crucial matters. Maas nods when the matter comes up. “Of course, privacy around data has been in the news a lot,” he says. “People care about what happens to their information. But, I think we can have a positive outlook on this. Public health truly is about the greater good.”
Maas emphasises the point by explaining how happy people are to share their information when asked to do so in hospitals if it means it can help others. He adds: “We actually already give consent so often when it comes to sharing data: your Apple Health app, Google calendar or Google search data. People clearly are happy to share their data if it means they get insights into their own health – or even a phone operating system - in return. So the trickier step is collating it all together in one place.”
Ultimately, Maas says that we need to make sure that the right parties are talking to each other to come up with useful solutions. “Although healthcare professionals work with data, they are not necessarily data scientists. And you also can’t just give a tech company healthcare data to sort out – healthcare comes with its own set of sensitive issues.”
In phones we trust
AI solutions in healthcare are already improving the well-being of citizens in the Amsterdam Area due to the combined efforts of experts in healthcare, machine learning and policy-making who are all focused on practical outcomes.
In the meantime, should we worry that our phones are spying on us and that robots are going to replace our physicians anytime soon? “I don’t think we need to worry about being replaced by robots for a very long time,” Maas chuckles. “For now, AI’s role will mainly be focused on supporting healthcare professionals, identifying patterns in data and speeding up medical processes. And of course your phone knows everything you do – it has known for the past five years. I think the interesting question is not ‘shall we share our data’, but rather ‘do you want only the Facebooks and the Googles that you pledged your data to, to decide what happens to your data, or would you rather also use your data for public health’ - which ultimately benefits yourself and the people you love.”
But Maas does admit to being excited about what the future might bring. “Research has pointed out it’s easier for us to admit that we smoke to our phones than it is to our physician,” he says. “How amazing is that! Now that we can compare this data, it’s also teaching us on the nuances in human interaction when it comes to health. We definitely need our healthcare professionals, but it’s promising there are so many things technology can do to help us become healthier citizens and live longer lives.”