Data-driven knowledge discovery from Brain Imaging of Alzheimer’s disease patients

Alzheimer’s disease (AD) is a chronic neurodegenerative disease which is largely responsible for dementia in around 6% of the population aged 65 and above. The availability of human brain data generated by imaging techniques, such as Magnetic Resonance Imaging, have resulted in a growing interest in data-driven approaches for the diagnosis of neurological disorders and for the identification of new biomarkers. The knowledge discovery process typically involves complex data workflows that combine pre-processing techniques, statistical methods, machine learning algorithms, post-processing and visualisation techniques. This talk presents specific research efforts in this direction, promising results, open issues and challenges.