OperaV1, Main, Exploration, bibRecord, 000367

Machine learning on brain MRI data for differential diagnosis of Parkinson's disease and Progressive Supranuclear Palsy.

Identifieur interne : 000367 ( Main/Exploration ); précédent : 000366; suivant : 000368

Machine learning on brain MRI data for differential diagnosis of Parkinson's disease and Progressive Supranuclear Palsy.

Auteurs : C. Salvatore [Italie] ; A. Cerasa [Italie] ; I. Castiglioni [Italie] ; F. Gallivanone [Italie] ; A. Augimeri [Italie] ; M. Lopez [Italie] ; G. Arabia [Italie] ; M. Morelli [Italie] ; M C Gilardi [Italie] ; A. Quattrone [Italie]

Source :

Journal of neuroscience methods ; 2014.

RBID : pubmed:24286700

English descriptors

Abstract

Supervised machine learning has been proposed as a revolutionary approach for identifying sensitive medical image biomarkers (or combination of them) allowing for automatic diagnosis of individual subjects. The aim of this work was to assess the feasibility of a supervised machine learning algorithm for the assisted diagnosis of patients with clinically diagnosed Parkinson's disease (PD) and Progressive Supranuclear Palsy (PSP).

DOI: 10.1016/j.jneumeth.2013.11.016
PubMed: 24286700

Affiliations:

Italie

Le document en format XML

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<author><name sortKey="Salvatore, C" sort="Salvatore, C" uniqKey="Salvatore C" first="C" last="Salvatore">C. Salvatore</name>
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<country xml:lang="fr">Italie</country>
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<author><name sortKey="Gilardi, M C" sort="Gilardi, M C" uniqKey="Gilardi M" first="M C" last="Gilardi">M C Gilardi</name>
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<author><name sortKey="Quattrone, A" sort="Quattrone, A" uniqKey="Quattrone A" first="A" last="Quattrone">A. Quattrone</name>
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<term>Corpus Callosum (pathology)</term>
<term>Diagnosis, Differential</term>
<term>Female</term>
<term>Humans</term>
<term>Image Interpretation, Computer-Assisted</term>
<term>Magnetic Resonance Imaging</term>
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<term>Mesencephalon (pathology)</term>
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<term>Parkinson Disease (pathology)</term>
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<term>Algorithms</term>
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<front><div type="abstract" xml:lang="en">Supervised machine learning has been proposed as a revolutionary approach for identifying sensitive medical image biomarkers (or combination of them) allowing for automatic diagnosis of individual subjects. The aim of this work was to assess the feasibility of a supervised machine learning algorithm for the assisted diagnosis of patients with clinically diagnosed Parkinson's disease (PD) and Progressive Supranuclear Palsy (PSP).</div>
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Machine learning on brain MRI data for differential diagnosis of Parkinson's disease and Progressive Supranuclear Palsy.

Machine learning on brain MRI data for differential diagnosis of Parkinson's disease and Progressive Supranuclear Palsy.

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English descriptors

Abstract

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Le document en format XML

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