Linked Life Data

9555629

Source:http://linkedlifedata.com/resource/pubmed/id/9555629

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
1998-7-7
pubmed:abstractText
Machine learning techniques can be used to extract knowledge from data stored in medical databases. In our application, various machine learning algorithms were used to extract diagnostic knowledge which may be used to support the diagnosis of sport injuries. The applied methods include variants of the Assistant algorithm for top-down induction of decision trees, and variants of the Bayesian classifier. The available dataset was insufficient for reliable diagnosis of all sport injuries considered by the system. Consequently, expert-defined diagnostic rules were added and used as pre-classifiers or as generators of additional training instances for diagnoses for which only few training examples were available. Experimental results show that the classification accuracy and the explanation capability of the naive Bayesian classifier with the fuzzy discretization of numerical attributes were superior to other methods and estimated as the most appropriate for practical use.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0148-5598
pubmed:author
pubmed:issnType
Print
pubmed:volume
21
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
429-44
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1997
pubmed:articleTitle
Induction of decision trees and Bayesian classification applied to diagnosis of sport injuries.
pubmed:affiliation
INFONET, Kranj, Slovenia.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't