Linked Life Data

15853566

Source:http://linkedlifedata.com/resource/pubmed/id/15853566

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2005-4-27
pubmed:abstractText
The current scientific model for clinical decision-making is founded on binary or Aristotelian logic, classical set theory and probability-based statistics. Evidence-based medicine has been established as the basis for clinical recommendations. There is a problem with this scientific model when the physician must diagnose and treat the individual patient. The problem is a paradox, which is that the scientific model of evidence-based medicine is based upon a hypothesis aimed at the group and therefore, any conclusions cannot be extrapolated but to a degree to the individual patient. This extrapolation is dependent upon the expertise of the physician. A fuzzy logic multivalued-based scientific model allows this expertise to be numerically represented and solves the clinical paradox of evidence-based medicine.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
1744-8360
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
4
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
249-54
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Fuzzy logic and causal reasoning with an 'n' of 1 for diagnosis and treatment of the stroke patient.
pubmed:affiliation
Department of Neurology, University of Illinois College of Medicine in Chicago, 912 South Wood Street, Room 855 N, Chicago, IL 60612, USA. helgason@uic.edu
pubmed:publicationType
Journal Article, Review