Patient-in-the-loop AI / Oncology
Design the journey.
Not just the explanation.
Our collaboration with Radboud University and Radboudumc explores how people can understand, question and use AI-supported information in conversations about care. Our involvement includes the ELSA collaboration and SIDN-supported research on responsible clinical decision support.
Start with the patient's priorities
We investigate patient journeys with patients, caregivers and professionals. We explore when people need information, which daily-life outcomes matter to them, how preferences change and where digital interaction might create an additional burden.
Make explanation an interaction
Our design direction goes beyond a single risk score. We explore conversational and visual formats for questions, options, uncertainty and the provenance of information. The aim is to support understanding and deliberation, not to steer a person's treatment choice.
Connect insight to working services
The expertise we bring includes inclusive service blueprints, accessible companion interfaces, low-burden patient-reported input, understandable feedback and software integration with professional systems. Sensory, cognitive and digital-literacy needs, assisted use and human oversight inform the design.
Keep learning in context
We contribute prototyping and iterative evaluation of comprehension, usability, acceptability and workflow fit, alongside implementation and exploitation planning. Clinical partners define clinical content and responsibilities; specialist partners provide and validate the underlying models.
Our role: making explainable AI usable.
ConnectedCare designs the interaction between patients, care professionals and AI-supported information. We explore which explanations people need, when they need them and how conversational and visual interfaces can support understanding and shared decision-making. We develop prototypes and evaluate their clarity, usability and fit with clinical workflows.
Research partners such as Radboud University develop and validate the underlying AI models. Together, we connect model explanations with the questions, priorities and decisions people face in everyday care.
Read the SIDN project profile ↗Explore the ELSA collaboration ↗