Geert Grooteplein Zuid 10, 6525 GA Nijmegen + Houtlaan 4, 6525 XZ Nijmegen
The Radboud AI for Health Lab centers its research on three core themes: clinical decision support and disease diagnosis, automated risk detection and treatment planning, and real-time operational assistance during surgery and interventions.
To drive these advancements, the lab leverages key technical AI components, focusing primarily on:
With a commitment to explainable, and responsible AI systems.
The Radboud AI for Health Lab is dedicated to bridging the gap between technical AI research and practical healthcare innovation.
The lab’s mission and vision are to build the fundamental knowledge base, technological tools, and human capacities necessary to solve pressing clinical problems and improve patient care through smart, tailored technology applied directly within hospitals and healthcare institutes.
The impact of the lab lies in accelerating a comprehensive digital transformation in healthcare, achieved by validating AI breakthroughs directly in live clinical settings alongside medical experts, offering hands-on education and courses for hospital personnel, and embedding privacy-compliant, ethical, and responsible AI frameworks to ensure trust and safety across the healthcare ecosystem.
MIHRacle: Multi-modal interactive health records – Investigates automatic methods to make the information from electronic patient records available in an interactive and comprehensible way for patients.
AI-driven genetic diagnosis for rare diseases – Developing a self-learning AI algorithm that can automatically detect patients with genetic diseases by using the more than 500 TB of available genetic data.
Unraveling mechanisms of vascular function and regulation with causal discovery – Focus on developing a data model that helps to discover links between vascular function and the brain, to predict the course of, among others, Alzheimer’s and complex vascular surgery.
AI-based treatment decision support in patients with chronic degenerative low back pain –Developing a decision support tool that helps patients and their caregivers to choose the best treatment for lower back pain.
Predictive modeling in the ICU Sepsis: central venous catheter infection appearance – Developing an algorithm for predicting the occurrence of a catheter infection in the Intensive Care Unit
Development and validation of a deep-learning system for wisdom tooth removal – AI-driven ‘flowchart’ for surgeons to prevent the unnecessary removal of wisdom teeth.
Radboud University (RU) is a general university in The Netherlands, active in almost all scientific fields, and one of the leading universities worldwide.
Radboud University Medical Center (Radboudumc) is the teaching hospital affiliated with the Radboud University, in the city of Nijmegen in the eastern-central part of the Netherlands.
