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

Abstract : 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.
Type de document :
Communication dans un congrès
ISMRM Workshop on Machine Learning Part II -2018, Oct 2018, Washington, United States
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https://hal-enac.archives-ouvertes.fr/hal-01998187
Contributeur : Laurence Porte <>
Soumis le : mercredi 20 février 2019 - 19:57:47
Dernière modification le : vendredi 22 février 2019 - 01:30:28

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  • HAL Id : hal-01998187, version 1

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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〉

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