A method for statistical learning in large databases of heterogeneous imaging, cognitive and behavioral data.

PosterInternational audienceThe aim of this study is to develop a generative and probabilistic statistical learning model for the joint analysis of heterogeneous biomedical data. The model will be applied to the investigation of neurological disorders from collections of brain imaging, body sensors, biological and clinical data available in current large-scale health databases. The resulting methodological framework will be tested on the UK Biobank, as well as on pathology-specific clinical data, as provided by the ADNI, or INSIGHT initiatives