Linked Life Data

2231194

Source:http://linkedlifedata.com/resource/pubmed/id/2231194

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
1990-12-12
pubmed:abstractText
A computer-aided morphometrical study was performed on histological specimens of reactive hyperplastic (n = 10) and malignant (n = 17) mesothelium. For each cell, seven nuclear features were measured and 13 parameters computed. Using stepwise variable selection, discriminant analysis chose the nuclear contour index, the standard deviation of the nuclear area, and the mean of the nuclear perimeter as discriminating features between hyperplastic and malignant mesothelium. The coefficients of these variables were included in a discriminant function which gave perfect discrimination between the two groups of lesions. When the function was assessed on a test set of hyperplastic (n = 10) and malignant (n = 17) mesothelial lesions treated as 'unknown', complete separation between these two diagnostic categories was achieved. This classification rule may help to increase the level of confidence with which a histological diagnosis of mesothelioma can be established.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0022-3417
pubmed:author
pubmed:issnType
Print
pubmed:volume
162
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
57-60
pubmed:dateRevised
2004-11-17
pubmed:meshHeading
pubmed:year
1990
pubmed:articleTitle
A morphometrically-based classification rule for the diagnosis of primary mesothelial lesions.
pubmed:affiliation
Department of Pathology, City Hospital, Alessandria, Italy.
pubmed:publicationType
Journal Article