Multi-class parkinsonian disorders classification with quantitative MR markers and graph-based features using support vector machines.

@article{Morisi2018MulticlassPD,
  title={Multi-class parkinsonian disorders classification with quantitative MR markers and graph-based features using support vector machines.},
  author={Rita Morisi and David Neil Manners and Giorgio Gnecco and Nico Lanconelli and Claudia Testa and Stefania Evangelisti and Lia Talozzi and Laura Ludovica Gramegna and Claudio Bianchini and Giovanna Calandra-Buonaura and Luisa Sambati and Giulia Giannini and Pietro Cortelli and Caterina Tonon and Raffaele Lodi},
  journal={Parkinsonism & related disorders},
  year={2018},
  volume={47},
  pages={64-70}
}
BACKGROUND AND PURPOSE In this study we attempt to automatically classify individual patients with different parkinsonian disorders, making use of pattern recognition techniques to distinguish among several forms of parkinsonisms (multi-class classification), based on a set of binary classifiers that discriminate each disorder from all others. METHODS We… CONTINUE READING