Litcius/Paper detail

Accuracy of MRI Classification Algorithms in a Tertiary Memory Center Clinical Routine Cohort

Morin, Alexandre, Samper-Gonzalez, Jorge, Bertrand, Anne, Ströer, Sébastian, Dormont, Didier, Mendes Aguiar Santos, Aline, Coupé, Pierrick, Ahdidan, Jamila, Lévy, Marcel, Samri, Dalila, Hampel, Harald, Dubois, Bruno, Teichmann, Marc, Epelbaum, Stéphane, Colliot, Olivier

2020Archive ouverte UNIGE (University of Geneva)25 citationsOpen Access PDF

Abstract

Automated volumetry software (AVS) has recently become widely available to neuroradiologists. MRI volumetry with AVS may support the diagnosis of dementias by identifying regional atrophy. Moreover, automatic classifiers using machine learning techniques have recently emerged as promising approaches to assist diagnosis. However, the performance of both AVS and automatic classifiers have been evaluated mostly in the artificial setting of research datasets. Objective: Our aim was to evaluate the performance of two AVS and an automatic classifier in the clinical routine condition of a memory clinic.

Topics & Concepts

Support vector machineArtificial intelligenceComputer scienceUnivariateDiagnostic accuracyMachine learningClassifier (UML)Pattern recognition (psychology)MedicineRadiologyMultivariate statisticsDementia and Cognitive Impairment ResearchCerebrovascular and Carotid Artery DiseasesNeurological Disease Mechanisms and Treatments