Predication of different stages of Alzheimer's disease using neighborhood component analysis and ensemble decision tree.

Journal: Journal of neuroscience methods

Published Date: Feb 24, 2018

Abstract

BACKGROUND: There is a spectrum of the progression from healthy control (HC) to mild cognitive impairment (MCI) without conversion to Alzheimer's disease (AD), to MCI with conversion to AD (cMCI), and to AD. This study aims to predict the different disease stages using brain structural information provided by magnetic resonance imaging (MRI) data.

Authors

Mingwu Jin

Department of Physics, University of Texas at Arlington, 502 Yates Street, Box 19059, Arlington, TX 76019, United States. Electronic address: mingwu@uta.edu.
Weishu Deng

Department of Physics, University of Texas at Arlington, 502 Yates Street, Box 19059, Arlington, TX 76019, United States.

Keywords

Alzheimer Disease Brain Cognitive Dysfunction Decision Trees Disease Progression Female Humans Image Interpretation, Computer-Assisted Machine Learning Magnetic Resonance Imaging Male Pattern Recognition, Automated Principal Component Analysis

External Resources

View on PubMed Access via DOI PubMed (29486213)

Predication of different stages of Alzheimer's disease using neighborhood component analysis and ensemble decision tree.

Abstract

Authors

Keywords

External Resources

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