Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
7
pubmed:dateCreated
1989-8-3
pubmed:abstractText
Complex decisions regarding the scope, efficiency, and effectiveness of service coupled with advances in microcomputer workstations and modeling software have created new incentives and opportunities for the application of powerful simulation methodologies in the clinical laboratory. Monte Carlo techniques that involve a large number of repetitive simulations of a system that has probabilistic characteristics may be especially useful. These techniques can be applied to problems where complex interactions, the nondeterministic nature of medical problems, and the incompleteness of medical knowledge render traditional analytic techniques impotent. Examples include complex clinical laboratory data analysis, clinical strategy development using advanced decision analysis methodologies, and prospective evaluation of the effects of proposed changes in laboratory operations. Although Monte Carlo simulation techniques appear to be promising for clinical laboratory use, limitations must be noted. Care and effort are required in model specification if meaningful results are to be obtained and their significance convincingly conveyed.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
AIM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
0003-9985
pubmed:author
pubmed:issnType
Print
pubmed:volume
113
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
750-7
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1989
pubmed:articleTitle
Monte Carlo simulation and the clinical laboratory.
pubmed:affiliation
Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis 55455.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S.