The Digital Health Consortium and IVADO are offering a series of Code @ santé workshops. These workshops promote knowledge sharing, use and discovery of modules and “packages” useful to the digital health community.
Guest : Pierre Bellec, Director of the functional neuroimaging unit, CRIUGM and Associate Professor, Department of Psychology, UdeM
Title of the workshop: Nilearn library: a bridge between neuroimaging and machine learning (with scikit-learn).
A useful library to load and visualize neuroimaging data, and also prepare the data to use other libraries. The tutorial also includes an application to detect age differences with functional imaging.
Biography of Pierre Bellec :
My initial training is in mathematics, modeling and image processing. My main research theme is the study of functional connectivity in distributed brain networks, at the system level, using an approach based on both real and simulated functional magnetic resonance imaging (fMRI) data.
I develop machine learning tools to study brain structure and function using magnetic resonance imaging. I use these tools to build computational models of brain function and explore brain reorganization processes in healthy aging and neurodegenerative diseases. I am co-leader of the imaging team of the Canadian Consortium on Neurodegeneration and Aging, and I am also a Junior 2 Scholar of the Fonds de recherche du Québec – Santé (FRQS). The main support for my lab comes from the Courtois Foundation, with additional support from NSERC, CIHR, FRQS, Brain Canada, Compute Canda, and the Lemaire Foundation.