The Applied AI Accelerator (A3) Lab centers its research on three core themes: predictive analytics and computer vision, generative AI, and agentic AI.
To drive these advancements, the lab leverages key technical AI components, focusing primarily on:
With a commitment to explainable and responsible AI systems.
The Applied AI Accelerator (A3) Lab is dedicated to bridging the gap between technical AI research and clinical practice.
The lab’s mission and vision are to accelerate the development, validation, and deployment of AI solutions that enhance patient outcomes, empower healthcare professionals, and create sustainable value for the healthcare system.
The impact of the lab lies in accelerating a comprehensive sociotechnical transition, achieved by validating breakthroughs directly in live clinical settings alongside healthcare and industrial partners, fostering multidisciplinary collaboration, and embedding explainable and responsible AI frameworks to build trust across the healthcare ecosystem.
Predictive Analytics and Computer Vision – Develops and clinically validates predictive tools and medical imaging models to assist clinicians in forecasting diagnosis, incidence, and risk, ultimately enabling personalized treatment selection.
Generative AI – Adapts and validates generative models (like Large Language Models and ambient listening tools) specifically for Dutch clinical workflows to automate documentation and significantly reduce administrative burden.
Agentic AI – Focuses on fine-tuning and validating proactive, (semi)autonomous multi-agent systems that coordinate complex clinical pathways and integrate predictive and generative tools safely into real-world hospital environments.
University of Groningen (RUG) is a leading academic institution that focuses on the theoretical development of AI, providing the essential scientific rigor, advanced methodologies, and academic framework for the lab’s PhD candidates.
University Medical Center Groningen (UMCG) is a prominent academic medical center that provides the direct financial funding, secure clinical data environment, and operational hospital setting required to test and validate the lab’s AI solutions in real-world workflows.
