Pattern recognition methods and applications in biomedical magnetic resonance

Multivariate statistical methods, sometimes termed as chemometrics or bio-informatics, have been used to extract information from high resolution nuclear magnetic resonance (NMR) spectra of biological samples. A promising approach for releasing information in such complex data sets lies in the power...

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Bibliographic Details
Published inProgress in nuclear magnetic resonance spectroscopy Vol. 39; no. 1; pp. 1 - 40
Main Authors Lindon, J.C., Holmes, E., Nicholson, J.K.
Format Journal Article
LanguageEnglish
Published 02.07.2001
Subjects
Algorithms
Knowledge based systems
Medical computing
Medical imaging
Pattern recognition
Statistical methods
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Summary:Multivariate statistical methods, sometimes termed as chemometrics or bio-informatics, have been used to extract information from high resolution nuclear magnetic resonance (NMR) spectra of biological samples. A promising approach for releasing information in such complex data sets lies in the power of computer pattern recognition algorithms. Thus, the combination of NMR spectroscopy with pattern recognition methods has the potential for generating relevant information and production of a significant knowledge base in many areas including understanding disease processes, assessing the effectiveness of therapies, and evaluating the side effects of drugs.
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ISSN:0079-6565
DOI:10.1016/S0079-6565(00)00036-4