Linked Life Data

15208193

Source:http://linkedlifedata.com/resource/pubmed/id/15208193

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2004-6-21
pubmed:abstractText
Fuzzy CoCo is a methodology, combining fuzzy logic and evolutionary computation, for constructing systems able to accurately predict the outcome of a human decision-making process, while providing an understandable explanation of the underlying reasoning. Fuzzy logic provides a formal framework for constructing systems exhibiting both good numeric performance (accuracy) and linguistic representation (interpretability). However, fuzzy modeling--meaning the construction of fuzzy systems--is an arduous task, demanding the identification of many parameters. To solve it, we use evolutionary computation techniques (specifically cooperative coevolution), which are widely used to search for adequate solutions in complex spaces. We have successfully applied the algorithm to model the decision processes involved in two breast cancer diagnostic problems, the WBCD problem and the Catalonia mammography interpretation problem, obtaining systems both of high performance and high interpretability. For the Catalonia problem, an evolved system was embedded within a Web-based tool-called COBRA-for aiding radiologists in mammography interpretation.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0077-8923
pubmed:author
pubmed:issnType
Print
pubmed:volume
1020
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
190-211
pubmed:dateRevised
2005-11-16
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Evolutionary fuzzy modeling human diagnostic decisions.
pubmed:affiliation
Swiss Federal Institute of Technology at Lausanne, EPFL, Logic Systems Laboratory, IN-Ecublens, CH-1015 Lausanne, Switzerland. carlos.pena@epfl.ch
pubmed:publicationType
Journal Article, Review