Support Vector Machine-based classification of Alzheimer's Disease population using a combination of structural MRI biomarkers

Sana Rebbah (1, 2) , Daniel Delahaye (1) , Stéphane Puechmorel (1) , Florence Nicol (1) , Pierre Maréchal (3) , Isabelle Berry (2)

1 ENAC - Ecole Nationale de l'Aviation Civile
2 ToNIC - Toulouse Neuro Imaging Center
3 IMT - Institut de Mathématiques de Toulouse UMR5219

Our study combines two extremely popular and current research topics, disease classification and supervised learning, which should be of interest to physicians and data scientists. Purpose/Introduction: The aim of this study is to investigate the early detection of Alzheimer's disease (AD) and mild cognitive impairment (MCI) conversion to AD using a combination of structural magnetic resonance imaging (sMRI) biomarkers.

Domaines: Informatique [cs]; Imagerie médicale; Informatique [cs]; Intelligence artificielle [cs.AI]

Sana Rebbah, Daniel Delahaye, Stéphane Puechmorel, Florence Nicol, Pierre Maréchal, et al.. Support Vector Machine-based classification of Alzheimer's Disease population using a combination of structural MRI biomarkers. ISMRM Workshop on Machine Learning Part II -2018, Oct 2018, Washington, United States. ⟨hal-01998187⟩