Discovering brain regions relevant to obsessivecompulsive disorder identification through bagging and transduction
We apply Machine learning techniques to identify subjects with OCD on the basis of their brain anatomy. The goal of OCD identification consists of automatically identifying brain regions related to the presence of the disorder. The voxels relevant for the disease identification are structured in small volume clusters. The areas are automatically found and they are in high agreement with previous works. This work can be easily extended to the characterization of other psychiatric disorders.
obsessivecompulsive disorder transduction machine learning mri voxel selection