Discovering Potential Clinical Profiles of Multiple Sclerosis from Clinical and Pathological Free Text Data with Constrained Non-negative Matrix Factorization.
Jacopo AcquarelliMonica BianchiniElena MarchioriPublished in: EvoApplications (1) (2016)
Keyphrases
- multiple sclerosis
- negative matrix factorization
- text data
- clinical trials
- text mining
- brain mri
- magnetic resonance images
- white matter
- document clustering
- magnetic resonance
- text documents
- text classification
- disease progression
- machine learning
- matrix factorization
- mr images
- structured data
- principal component analysis
- high dimensional
- image segmentation
- information retrieval systems