NDLI: Identification of patterns of gray matter abnormalities in schizophrenia using source-based morphometry and bagging

Content Provider	IEEE Xplore Digital Library
Author	Castro, E. Gupta, C.N. Martinez-Ramon, M. Calhoun, V.D. Arbabshirani, M.R. Turner, J.
Copyright Year	2014
Description	Author affiliation: Mind Res. Network, Albuquerque, NM, USA (Castro, E.; Gupta, C.N.; Calhoun, V.D.; Arbabshirani, M.R.) \|\| Electr. & Comput. Eng. Dept., Univ. of New Mexico, Albuquerque, NM, USA (Martinez-Ramon, M.) \|\| Dept. of Psychol., Georgia State Univ., Atlanta, GA, USA (Turner, J.)
Abstract	Despite its reliable diagnosis, schizophrenia lacks an objective diagnostic test or a validated biomarker, which prevents a better understanding of this disorder. Structural magnetic resonance imaging (sMRI) has been vastly explored to find consistent abnormality patterns of gray matter concentration (GMC) in schizophrenia, yet we are far from having reached conclusive evidence. This paper presents a machine learning approach based on resampling techniques to find brain regions with consistent patterns of GMC differences between healthy controls and schizophrenia patients, these regions being detected by means of source-based morphometry. This work uses multi-site data from the Mind Clinical Imaging Consortium, which is composed of sMRI data from 124 controls and 110 patients. Our method achieves a better classification rate than other algorithms and detects regions with GMC differences between both groups that are consistent with several findings on the literature. In addition, the results obtained on data from multiple sites suggest that it may be possible to replicate these results on other datasets.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	1513
Ending Page	1516
File Size	849866
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6943889
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Loading Bagging Accuracy Imaging Educational institutions Matrix decomposition
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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