Promoting efficiency and governance in healthcare with clinical AI solutions

Assessing X-rays or scans before deciding on diagnosis and treatment is a resource-intensive practice. It typically involves two independent radiologists, which is a challenge in Denmark today due to an acute shortage of radiologists. The Capital Region of Denmark and several private companies, including 2021.AI, have launched the Clinical Imaging Consortium (CLIC) project to solve this challenge by developing and operating state-of-the-art AI solutions that support radiologists in assessing and analyzing images in compliance with current regulations.


2021.AI is excited to be part of the Clinical Imaging Consortium (CLIC) project. The goal of this ambitious endeavor is to create a better framework for developing, testing, and validating AI solutions used for analyzing and interpreting X-ray and scanned images. This will ease the workload of radiologists and help ensure that patients receive the highest quality treatment possible.

Because radiology is a highly data-driven practice dependent on visual interpretation, AI-enabled software and solutions hold significant potential in clinical applications. Currently, many AI solutions have been deployed across all major medical imaging modalities, enabled by deep learning through which complex tasks, such as identifying an abnormality in a CT and MR scan, can be performed quickly and accurately. As the AI opportunities for radiology continue to grow, many radiologists and other clinicians are eager to understand and work with the new AI-enabled solutions and digital tools that could enable them to work more efficiently, allow more time for collaboration with other members of the patient’s care team, and ultimately, to impact diagnostics and treatment.

There are approximately 600 radiologists in Denmark. The CLIC project aims at accelerating the use of imaging-based AI decision support. Suppose that the workload for processing clinical images can be reduced by just five hours every week; this would be the equivalent of gaining 71 extra full-time radiologists a year in Denmark.

However, the health space faces challenges in delivering these clinical AI solutions to support radiologists. The roadblocks derive from lengthy and costly time to market for developing clinical AI solutions due to limited access to health data and annotated image data, and the availability of expert radiologists to perform the manual annotation is in short supply. In recent years, this has caused many AI initiatives to remain pilot projects, i.e., never to be implemented in daily operations. Furthermore, regulations such as GDPR and MDR and announced AI regulations make it challenging to get AI models approved and operational in the current environment.


Governing emerging technology systems to ensure compliance

The need to adhere to and document compliance with all relevant standards and regulatory requirements will be the subset of the CLIC project that 2021.AI will be responsible for. Via their AI platform GRACE, 2021.AI will deliver their comprehensive Governance, Risk Management, and Compliance (GRC) expertise for emerging tech to ensure compliance with any guidelines, requirements, and regulations.

With ready-to-apply impact assessments, rules & requirements, and certifications for various regulatory frameworks, GRACE makes it easy to build policy-guided workflows and guardrails into the AI development process to ensure adherence with regulations. Having GRC capabilities at the heart of AI innovations helps reduce risk and allows organizations to focus on their core goals for implementing new technologies.

Overview of project

  • Map the data landscape for image data and other health data in Denmark required for building data lakes that can support the development, testing, and implementation of AI solutions.
  • Clarify regulatory requirements for building and accessing such data lakes hosted by Danish regions and develop and implement an action plan for streamlining the process for obtaining regulatory approval to develop AI solutions based on the data lakes.
  • Build a model for One-Stop-Shop offering access to data lakes and services that will enable a shorter time to market for image-based AI solutions through more effective development and validation of AI solutions in a public-private partnership.
  • Deploy an AI data model by building individual data lakes in collaboration with Region H.
  • Test the value creation potential of the One-Stop-Shop against a range of different image-based AI solutions currently under development.
  • Integrate the CLIC One Stop Shop with the One-Stop-Shop in the OSCAR project, thus realizing significant synergies and ensuring the political, financial, and data-ethical sustainability of the CLIC project upon completion.
  • Share the results of the CLIC project to encourage the implementation of similar One-Stop-Shops in all Danish Regions.

A strong partner team will ensure successful implementation

The consortium consists of several private Danish companies; Radiology AI Test Center, DataFair, Enversion, Teal Medical, Siemens Healthcare, Radiobotics, Cerebriu, Roche, and 2021.AI. These companies were invited to be part of the CLIC project because they are leaders in either providing access to health data or in developing image-based AI solutions. The shared vision of the CLIC Project partners is to build a robust public-private partnership behind a One-Stop-Shop that can accelerate the development and implementation of imaging-based AI solutions in the Danish healthcare sector for the benefit of patients. The One-Stop-Shop will facilitate collaboration between private companies offering AI solutions and the public health care system that wants to integrate the AI solutions into the clinical workflow.

About CLIC

CLIC (Clinical Imaging Consortium) is rooted in a public-private partnership. The Innovation Fund provides DKK 14 million DKK for the project, which has a total budget of DKK 25 million and is to be completed in 2024. CLIC aims to develop a sustainable data model that will enable faster and easier access to the market for image-based AI solutions through more efficient development and validation of AI solutions in a public-private partnership. The project is led by a steering group consisting of both public and private partners: RAIT – Radiological Artificial Intelligence Test Center, Capital Region, DataFair ApS, Enversion A / S, Teal Medical ApS, Siemens Healthcare A / S, Radiobocs ApS, Cerebriu A / S, 2021.AI ApS and Roche Pharmaceuticals A / S. For more information, visit

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