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My work is focused on the impact of disease and treatment on brain structure and function of children and young adults, which is organized in research lines:

Neuroscientific outcome measurement

Focused on the development and application of neuroscientific outcome measurements, assessing neurocognitive functioning in children and adults (e.g. the in-house developed ‘Emma Toolbox for Neurocognitive Functioning’), advanced analysis of neurocognitive test performance (e.g. neurocognitive networks), structural and functional brain networks (e.g. DTI resting-state fMRI), and early neurocognitive functioning in babies and infants (e.g. eye-tracking).  

Clinical outcome prediction for precision medicine

Contributing to the transition towards precision medicine by improving clinical outcome prediction. Together with prof. dr. Mark Hoogendoorn & dr. Frank Bennis, we investigate the added value of machine learning models for clinical outcome prediction. We are also developing a machine learning pipeline optimized for high-dimensional data.

Data-driven health care innovation

Focused on the development of structured multidisciplinary clinical (follow-up) programs that make use of structured electronic clinical registration and integrate with other clinical data sources (e.g. medical devices, patient reported outcome measurements). Consequently, the structured clinical data flows into rich and ever-accumulating databases that are re-used for care evaluation and scientific research aimed at data-driven care innovation.

Neuroscience, Pediatrics, Traumatic Brain Injury, Data-driven health care innovation, Health intelligence