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Abstract #0402

Exploring Brain Connectivity in Ageing Using Explainable Deep Learning

Tamar van Asch1, Nathan De Jong1, Walter Backes1, Sebastian Köhler 2, Martin van Boxtel2, Miranda Schram3, and Jacobus Jansen1
1Radiology, Maastricht University Medical Center, Maastricht, Netherlands, 2Psychiatrie & Neuropsychologie, School for Mental Health and Neuroscience, Maastricht, Netherlands, 3Internal Medicine, Maastricht University, Maastricht, Netherlands


There is a growing need for the understanding of the process of ageing and the ability to predict who is at risk of neurodegenerative diseases and mortality. This study aims to develop and train a convolutional neural network on structural brain connectivity data to predict age. dMRI is used to map the structural connectivity of the brain. The dataset comprises 3494 subjects from The Maastricht Study, a cohort study of individuals aged between 40 and 77 years. Brain age prediction on the test set resulted in a Pearson’s correlation coefficient of 0.70 and a mean absolute error of 5.1 years.

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