S. Cha, Comprehensive Survey on Distance/Similarity Measures Between Probability Density Functions, International Journal Of Mathematical Models And Methods In Applied Sciences, vol.1, issue.4, pp.300-307, 2007.

M. Cercignani, Mean diffusivity and fractional anisotropy histograms of patients with multiple sclerosis, AJNR. American journal of neuroradiology, vol.22, issue.5, pp.952-958, 2001.

J. Dehmeshki, Magnetisation transfer ratio histogram analysis of primary progressive and other multiple sclerosis subgroups, Journal of the Neurological Sciences, vol.185, issue.1, pp.11-17, 2001.
DOI : 10.1016/s0022-510x(01)00447-6

P. P. Kwok, Predicting Clinically Definite Multiple Sclerosis from Onset Using SVM, Lecture Notes in Computer Science, pp.116-123, 2012.
DOI : 10.1007/978-3-642-34713-9_15

O. Querbes, Early diagnosis of Alzheimer's disease using cortical thickness: impact of cognitive reserve, Brain: A Journal of Neurology, vol.132, pp.2036-2047, 2009.

M. D. Steenwijk, Cortical atrophy patterns in multiple sclerosis are non-random and clinically relevant, Brain: A Journal of Neurology, vol.139, pp.115-126, 2016.
DOI : 10.1093/brain/awv337

URL : https://academic.oup.com/brain/article-pdf/139/1/115/17348705/awv337.pdf

A. Tourbah, MD1003 (high-dose biotin) for the treatment of progressive multiple sclerosis: A randomised, double-blind, placebo-controlled study, Multiple Sclerosis, pp.1719-1731, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01414958

V. Wottschel, Supervised machine learning in multiple sclerosis: applications to clinically isolated syndromes'. Doctoral, 2017.