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

Machine Learning Approach for Classifying Multiple Sclerosis Courses by Combining Clinical Data with Lesion Loads and Magnetic Resonance Metabolic Features

(2017) Adrian Ion-Mărgineanu et al.   Frontiers in Neuroscience

Resting-State fMRI in MS: General Concepts and Brief Overview of Its Application

(2015) Emilia Sbardella et al.   Biomed Research International

Multivariate pattern classification of gray matter pathology in multiple sclerosis

(2012) Kerstin Bendfeldt et al.   NEUROIMAGE

Classifying minimally disabled multiple sclerosis patients from resting state functional connectivity

(2012) Jonas Richiardi et al.   NEUROIMAGE

Diffusion tensor MRI tractography and cognitive impairment in multiple sclerosis

(2012) S. Mesaros et al.   NEUROLOGY

Comparison of random forest, support vector machine and back propagation neural network for electronic tongue data classification: Application to the recognition of orange beverage and Chinese vinegar

(2012) Miao Liu et al.   SENSORS AND ACTUATORS B-CHEMICAL

Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria

(2011) Chris H. Polman et al.   ANNALS OF NEUROLOGY

An application of Random Forests to a genome-wide association dataset: Methodological considerations & new findings

(2010) Benjamin A Goldstein et al.   BMC GENETICS

Computer-aided detection of multiple sclerosis lesions in brain magnetic resonance images: False positive reduction scheme consisted of rule-based, level set method, and support vector machine

(2010) Daisuke Yamamoto et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Evidence for CRHR1 in multiple sclerosis using supervised machine learning and meta-analysis in 12 566 individuals

(2010) Farren B.S. Briggs et al.   HUMAN MOLECULAR GENETICS

Comparison of multivariate classifiers and response normalizations for pattern-information fMRI

(2010) Masaya Misaki et al.   NEUROIMAGE

Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief

(2010) P.K. Douglas et al.   NEUROIMAGE

Introduction to machine learning for brain imaging

(2010) Steven Lemm et al.   NEUROIMAGE

Machine learning approach identifies new pathways associated with demyelination in a viral model of multiple sclerosis

(2009) Reiner Ulrich et al.   JOURNAL OF CELLULAR AND MOLECULAR MEDICINE

Multiple Sclerosis: MicroRNA Expression Profiles Accurately Differentiate Patients with Relapsing-Remitting Disease from Healthy Controls

(2009) Andreas Keller et al.   PLoS One

A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification

(2008) Alexander Statnikov et al.   BMC BIOINFORMATICS

Resting state sensorimotor functional connectivity in multiple sclerosis inversely correlates with transcallosal motor pathway transverse diffusivity

(2008) Mark J. Lowe et al.   HUMAN BRAIN MAPPING

Abnormal connectivity of the sensorimotor network in patients with MS: A multicenter fMRI study

(2008) Maria A. Rocca et al.   HUMAN BRAIN MAPPING

Multivariate analysis of fMRI time series: classification and regression of brain responses using machine learning

(2008) Elia Formisano et al.   MAGNETIC RESONANCE IMAGING

A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data

(2008) Vince D. Calhoun et al.   NEUROIMAGE

Machine learning classifiers and fMRI: A tutorial overview

(2008) Francisco Pereira et al.   NEUROIMAGE

Alemtuzumab vs. Interferon Beta-1a in Early Multiple Sclerosis

(2008)   NEW ENGLAND JOURNAL OF MEDICINE

Functional cortical changes of the sensorimotor network are associated with clinical recovery in multiple sclerosis

(2007) Domenico M. Mezzapesa et al.   HUMAN BRAIN MAPPING