Deriving biomedical diagnostics from NMR spectroscopic data

Download	View accepted manuscript: Deriving biomedical diagnostics from NMR spectroscopic data (PDF, 1.4 MiB)
DOI	Resolve DOI: https://doi.org/10.1007/s12551-011-0045-8
Author	Search for: Smith, Ian C. P.¹; Search for: Somorjai, Ray L.¹
Affiliation	National Research Council of Canada. NRC Institute for Biodiagnostics
Format	Text, Article
Subject	Biomedical spectroscopy; Statistical classification strategy (SCS); Soft independent modelling of class analogies (SIMCA); Cancer screening; 1H NMR spectra
Abstract	Biomedical spectroscopic experiments generate large volumes of data. For accurate, robust diagnostic tools the data must be analyzed for only a few characteristic observations per subject, and a large number of subjects must be studied. We describe here two of the current data analytic approaches applied to this problem: SIMCA (principal component analysis, partial least squares), and the statistical classification strategy (SCS). We demonstrate the application of the SCS by three examples of its use in analyzing 1H NMR spectra: screening for colon cancer, characterization of thyroid cancer, and distinguishing cancer from cholangitis in the biliary tract.
Publication date	2011-03-08
In	Biophysical Reviews 3, no. 1 (8 March 2011): 47–52.
Language	English
Peer reviewed	Yes
NPARC number	19703837
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Record identifier	6aaae1db-d99e-47c6-8480-da7a81d50a37
Record created	2012-03-28
Record modified	2020-04-21