Among the areas that are adopting AI the fastest are life sciences and medicine, both in the clinical and research fields, through national efforts and multi-nation collaborations. While each innovation that enters the market seems to take less time to be adopted – as evidenced by how quickly cell phones became indispensable – AI is setting new records.

“The steam engine and electricity took decades to become part of daily life,” says Christian Guttmann, Professor at Karolinska Institutet and Executive Director of the Nordic AI Institute, who focuses his research on AI use in health, medicine and pharmaceuticals. “Generative AI took only two months to reach 100 million users.”

Generative AI took only two months to reach 100 million uses.

An established discipline

For Christian Guttmann, who has studied and applied AI, machine learning and multi-agent systems in healthcare for several decades, the explosion of AI applications is not surprising. A scientist, entrepreneur and businessman, he was named one of the top 100 AI global leaders in 2019. Life science/medical areas with the most opportunities for AI use include drug development, research and diagnoses, he believes.

We can use AI to match molecules to pathogens, manage chronic diseases and in healthcare to look at patterns of certain conditions. It will lead to major advancements in healthcare operations and services, and doctors and hospitals will benefit from better delivery of services.”

“In the Nordic countries, it is an established discipline,” Guttmann says. “In part this is because so much information is already digitized. We can use AI to match molecules to pathogens, manage chronic diseases and in healthcare to look at patterns of certain conditions. It will lead to major advancements in healthcare operations and services, and doctors and hospitals will benefit from better delivery of services.”

AI also has been used to identify additional uses for drugs other than their original purpose and to track the long-term well-being of patients. “There is very accurate data around quality registries and very accurate information about people’s health outcomes,” Guttmann says. “When we combine that knowledge, we aim to use it for real-world evidence.”

Nordic initiatives

Think tanks in different countries continue to study more uses for AI in the life sciences and medical fields. Sweden has invested USD 1 billion in Hagastaden in Stockholm, a city district fostering life science research and entrepreneurship through a collaboration of businesses, healthcare and university professionals. SciLifeLab & Wallenberg National Program for Data-Driven Life Science is a 12-year, SEK 3.1 billion project charged in part with training life scientists to use data more efficiently.

An initiative to improve diagnoses of brain ailments at HUS Helsinki University Hospital in Finland, in conjunction with local corporations, has led to the development of an algorithm that can identify potentially deadly intracerebral hemorrhages by reviewing images. The next goal is to create a formula that can pinpoint all sudden intracerebral hemorrhages.

In other nations, Norway is revamping its healthcare system and looking for ways to apply AI, while Denmark is exploring how AI can help manage its homecare programs, notes Guttmann.

The hope is to position the Nordic countries at the forefront when it comes to ethical AI and responsible use of health data.”

Nordic Innovation initiatives go even deeper into AI uses. A three-year project is underway to create and showcase an ethical algorithm capable of reading digital and analog patient journals, from different countries and health systems, as well as in different languages. Besides the primary goal of simplifying access to records, while maintaining patient privacy, the hope is to position the Nordic countries at the forefront when it comes to ethical AI and responsible use of health data.

Christian Guttmann, Professor, Karolinska Institutet, Executive Director, Nordic AI Institute

Implementation and data protection

One of the challenges of implementing AI in healthcare is the disconnect between technology and medicine. While big technology companies can produce innovations quickly, implementing them in hospitals and medical settings can take much longer.

Privacy and data protection also remain key concerns in AI use, especially when it comes to personal information. Some healthcare professionals worry about a lack of transparency and provenance when AI is applied in healthcare settings. While the results are often superior to those produced by a human, there is concern about the inability to see all the steps that led to the outcome. “They want very accurate traceability,” Guttmann says. “That concern should be balanced against the benefits of using AI.”

Generative AI certainly is the opportunity to identify major trends.”

Christian Guttmann continues to see a strong future for AI.

“We’ll be looking at outcomes of health operations and delivery, to track the journey of a patient,” he says. “Generative AI certainly is the opportunity to identify major trends.”