Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects

Mild cognitive impairment (MCI) is a transitional stage between age-related cognitive decline and Alzheimer's disease (AD). For the effective treatment of AD, it would be important to identify MCI patients at high risk for conversion to AD. In this study, we present a novel magnetic resonance i...

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Bibliographic Details
Published in:	NeuroImage (Orlando, Fla.) Vol. 104; pp. 398 - 412
Main Authors:	Moradi, Elaheh, Pepe, Antonietta, Gaser, Christian, Huttunen, Heikki, Tohka, Jussi
Format:	Journal Article
Language:	English
Published:	United States Elsevier Inc 01.01.2015 Elsevier Limited
Subjects:	ADNI Age Aged Aged, 80 and over Aggregates Alzheimer Disease - pathology Alzheimer's disease Biomarkers Brain - pathology Classification Cognitive Dysfunction - pathology Conversion Databases, Factual Diagnosis Early diagnosis Feature selection Female Humans Image Interpretation, Computer-Assisted - methods Learning Low density separation Machine Learning Magnetic resonance imaging Magnetic Resonance Imaging - methods Male Medical imaging Middle Aged Mild cognitive impairment NMR Nuclear magnetic resonance Patients Risk Factors Semi-supervised learning Studies Support vector machine ADNI Feature selection Early diagnosis Magnetic resonance imaging Mild cognitive impairment Semi-supervised learning Classification Low density separation Support vector machine Alzheimer's disease
ISSN:	1053-8119, 1095-9572, 1095-9572
Online Access:	Get full text
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