Evaluation of machine learning algorithms performance for the prediction of early multiple sclerosis from resting-state FMRI connectivity data.

Machine Learning application on clinical data in order to support diagnosis and prognostic evaluation arouses growing interest in scientific community. However, choice of right algorithm to use was fundamental to perform reliable and robust classification. Our study aimed to explore if different kin...

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Publicado en:	Brain Imaging & Behavior Vol. 13; no. 4; pp. 1103 - 1115
Autores principales:	Saccà, Valeria, Sarica, Alessia, Novellino, Fabiana, Barone, Stefania, Tallarico, Tiziana, Filippelli, Enrica, Granata, Alfredo, Chiriaco, Carmelina, Bruno Bossio, Roberto, Valentino, Paola, Quattrone, Aldo
Formato:	research Journal Article
Publicado:	Springer Nature Aug2019
Acceso en línea:	Ver este registro en EBSCOhost