Radboud University Medical Center Leads Innovation, Integrates AI-powered Radiology for Enhanced Patient Care

Update: Harrison.ai Radiology solutions were previously marketed as Annalise.ai.

Nijmegen, Netherlands — Radboud university medical center (Radboudumc) has been leading the way in advanced medical imaging by adopting advanced AI-based image analysis solutions. The latest being the adoption of Annalise.ai’s technology for brain CTs and chest X-rays, into their radiology practice. This deployment also marks the entry of leading imaging AI provider, annalise.ai into the Dutch healthcare market.

Accurate and timely radiology reporting is essential for effective diagnostic decisions and patient care—it can even save lives. However, subtle findings, particularly in chest and brain imaging, are sometimes overlooked. This is especially true in high-pressure environments like emergency rooms, where every minute counts, or when radiologists face overwhelming workloads due to staffing shortages. In such situations, AI-powered solutions, like Annalise’s tools for non-contrast CT brain (CTB) and chest X-ray (CXR), provide much-needed support for radiologists and clinicians.

“No radiology finding should be missed just because of a high workload,” emphasised Prof. Mathias Prokop, Head of Radboudumc Department of Medical Imaging. “We must unleash the potential of AI to empower our staff in making quick and accurate decisions.” “Automated assessment of radiological images and worklist triaging also holds value in freeing manpower for those areas in patient care where an expert human touch is most needed”.

The decision to add comprehensive and customisable AI-backed solutions to Radboudumc Radiology services aligns with its mission to have a significant impact on health and healthcare in an innovative and patient-centric manner.

“Radboudumc remains the birthplace for breakthroughs. We focus on implementing innovations that improve quality of care while keeping healthcare affordable and making sure our professionals can cope with the increasing demand in diagnostic procedures,” added Prof. Prokop.

Annalise Enterprise CXR is a comprehensive decision-support tool that can detect up to 124 chest X-ray findings, while Annalise Enterprise CTB identifies up to 130 findings from non-contrast head CT studies within a few minutes. The tools are streamlining diagnostic processes around the world, enabling radiologists and healthcare practitioners to prioritize and triage urgent cases and make confident, rapid decisions.

“As a strong believer in the power of AI to improve imaging diagnostics, and increase efficiency in healthcare, I am curious about how Annalise’s CTB and CXR solutions will transform Radboudumc’s radiology. With heightened efficiency and precision, rapid detection turnaround time, and a second opinion in seconds, the tools are ready to change the game for our patients and radiologists alike,” said Prof. Prokop.

In addition to adopting these solutions, Radboudumcis is launching a multi-year research project with other hospitals to demonstrate AI’s impact across Dutch healthcare in both academic and general public hospital environments. In line with Radboudumc’s key principle of “Turning ambition to impact”, the study will evaluate the impact of these tools on workflow enhancements, setting the stage for broader adoption in the Netherlands and potentially across Europe.

“The deployment of Annalise into clinical practise at Radboudumc and other hospitals enables world-leading research to be conducted and demonstrates the clinical and economic benefit Annalise is providing.  It’s a seed that we are sowing, the fruits of which could reshape the future of healthcare in the Netherlands—and perhaps the continent,” said Dimitry Tran, deputy CEO and co-founder, annalise.ai. As a primary reference site for hospitals across the Netherlands and Europe, Radboudumc is poised to lead the new era of integrating AI into clinical practice, strengthening the foundation for a more efficient, accurate, and patient-centered healthcare system.