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28 November 2024

Visit from the Minister: Danish digital research as a driving force

Artificial Intelligence and humans are better together than apart. On a sunny autumn day in November, Minister for Digitalization Caroline Stage Olsen and Chairman of the Health Committee in the Capital Region of Denmark Christoffer Buster Reinhardt got a first-hand look at CAMES, a simulation training center at Rigshospitalet. Here, DIREC had invited them to a talk about how the center is working to make Denmark one of the leading countries in Europe within digital research and innovation.

Thomas Riisgaard Hansen, Director of DIREC, shared three key recommendations with the Minister:

  1. Unite Denmark’s digital research and innovation ecosystem

    By aligning Denmark’s diverse initiatives, we can unlock powerful synergies that amplify efforts and multiply outcomes.
  2. Invest broadly in emerging digital technologies

    While AI dominates current focus, other transformative technologies may take the lead by 2030. Denmark must priortize AI development while fostering a broad base of innovation to ensure long-term growth and adaptability.
  3. Leverage Denmark’s unique strengths to drive growth and enhance public solutions
    Rather than emulating Silicon Valley, Denmark should build on its own research and industrial strengths to create distinctive successes. Strategic, targeted investments in these areas will deliver the greatest impact.
AI as a mentor in healthcare

The Minister was also introduced to a concrete example of how research, innovation, and entrepreneurship can converge. Professors Aasa Feragen and Martin G. Tolsgaard presented the Explain Me project, funded by DIREC.
 
This collaboration between researchers from DTU, KU and clinicians at CAMES explores how artificial intelligence can serve as a mentor for less experienced healthcare professionals. AI provides guidance to perform high-quality scans, reducing the need for advanced expertise.

Currently, significant disparities exist in the quality of ultrasound scans for pregnant women. Clinicians often struggle to identify high-risk pregnancies that require timely intervention. This highlights the need for standardized ultrasound quality across practitioners and hospitals.
 
By leveraging AI-driven decision support systems and explainable AI models, the project has achieved signifcant advancements in diagnosing high-risk pregnancies. For instance, the technology can detect nearly 25% more cases of premature birth risk — a condition that poses serious dangers to infants and is costly for the healthcare system.
 
The promising outcomes of the Explain Me project have led to the establishment of a spinout company, Prenaital, dedicated to commercializing this research and making it accessible in clinical settings.

Learn more about the Explain Me project here.