Linked Life Data

19163741

Source:http://linkedlifedata.com/resource/pubmed/id/19163741

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2009-2-16
pubmed:abstractText
We aim to identify subtypes of diseases like Osteoarthritis (OA) and Parkinson's Disease (PD) that present clinical heterogeneity. We do so by searching for homogeneous clusters in values of markers that reflect the severity of the disease. In the current paper we consider two important items for a cluster analysis. First, as time can contribute largely to the measured variability in the data, we search for the most appropriate way to adjust for it. Second, as we aim for reliable cluster analyses, cluster results should exhibit robustness to little change in the data. To investigate these issues, we transform the data by adding noise of different levels before cluster modeling and we rely on a chi(2)-based measure of association to compare cluster results for different types of time adjustment. The results of our experiments suggest to adjust data for a logarithmic age effect for OA and a square root effect of the disease duration for PD because these adjustments lead more reliable cluster results.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1557-170X
pubmed:author
pubmed:issnType
Print
pubmed:volume
2008
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
4601-4
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Reliability of cluster results for different types of time adjustments in complex disease research.
pubmed:affiliation
LIACS, Leiden University, THE NETHERLANDS. fcolas@liacs.nl
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't