CAIDX Project: Best Practices for the Development and Implementation of Diagnostics AI in European Hospitals

In recent years, the development of artificial intelligence (AI) algorithms and tools in medicine has increased significantly. These advances have the potential to greatly improve healthcare. However, the adoption of AI into routine clinical practice in European hospitals is currently at an early stage of development.

CAIDX (acronym for Clinical AI-based Diagnostics) project aims to facilitate the uptake of AI and data-driven diagnostic tools in hospitals by involving different stakeholders in the process. By interviewing different stakeholder groups, we aim to identify best practices and challenges for developing and implementing AI based diagnostic tools for clinical use.

In the early stages of the project, we are focusing on finding answers to questions such as What are the main challenges? Are there already best practices for public-private collaboration? What can we learn from companies and early adopters?

“We are currently interviewing different stakeholders, such as AI developers, implementation specialists and clinicians to gain a deeper understanding of the implementation of AI based solutions,” tells Monica Recabarren, CAIDX Project Leader, Aalborg University Hospital. “The first interviews have revealed that in the implementation phase, it is important to focus on the purpose of the new AI based solution, to ensure involvement of all relevant employees and to address any concerns of the users from the very beginning.”

If you are a relevant stakeholder and would also like to contribute by sharing your challenges and best practices on AI development and implementation, please contact us!

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