Unsupervised learning based feature extraction for differential diagnosis of neurodegenerative diseases: A case study on early-stage diagnosis of Parkinson disease.

Journal: Journal of neuroscience methods

Published Date: Aug 21, 2015

Abstract

BACKGROUND: The development of MRI based methods could prove extremely valuable for identification of reliable biomarkers to aid diagnosis of neurodegenerative diseases (NDs). A great deal of current research has been aimed at identification biomarkers for both diagnosis at early stage and evaluation of the progression of NDs.

Authors

Gurpreet Singh

Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore 117585, Singapore.
Lakshminarayanan Samavedham

Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore 117585, Singapore; Residential College 4, 8 College Avenue West, #02-16W, Education Resource Centre, Singapore 138608, Singapore. Electronic address: laksh@nus.edu.sg.

Keywords

Adult Brain Databases, Factual Diagnosis, Differential Disease Progression Early Diagnosis Humans Image Interpretation, Computer-Assisted Least-Squares Analysis Magnetic Resonance Imaging Middle Aged Parkinson Disease Sensitivity and Specificity Support Vector Machine

External Resources

View on PubMed Access via DOI PubMed (26304693)

Unsupervised learning based feature extraction for differential diagnosis of neurodegenerative diseases: A case study on early-stage diagnosis of Parkinson disease.

Abstract

Authors

Keywords

External Resources

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