LABS
Laboratory of AI & Biomedical Science
MLNI is a python package that performs various tasks using neuroimaging data: i) binary classification for disease diagnosis, following good practice proposed in AD-ML; ii) regression prediction, such as age prediction; and iii) semi-supervised clustering with HYDRA.
SOPNMF is the stochastic implementation of the Orthogonal Projective Non-negative Matrix Factorization (OPNMF) that can be scaled to large-scale imaging data for clinically interpretable feature extraction.
MAGIC, Multi-scAle heteroGeneity analysIs and Clustering, is a multi-scale semi-supervised clustering method that aims to derive robust clustering solutions across different scales for brain diseases.