Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1993-12-7
pubmed:abstractText
Pattern recognition has been applied to the analysis of in vivo 31P NMR spectra. Using four different classes of tumour and three types of normal tissue, cluster analysis and artificial neural networks were successful in separating and classifying the majority of samples analysed. Although the phosphomonoester and P(i) regions appeared to be the most important spectral features, data representing the entire 31P spectrum were required for best separation of the tumour and tissue classes.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
0952-3480
pubmed:author
pubmed:issnType
Print
pubmed:volume
6
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
237-41
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:articleTitle
Pattern recognition of 31P magnetic resonance spectroscopy tumour spectra obtained in vivo.
pubmed:affiliation
Division of Biochemistry, St George's Hospital Medical School, London, UK.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't