Induction of decision trees and Bayesian classification applied to diagnosis of sport injuries.
J Med Syst
; 21(6): 429-44, 1997 Dec.
Article
em En
| MEDLINE
| ID: mdl-9555629
ABSTRACT
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.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Traumatismos em Atletas
/
Árvores de Decisões
/
Teorema de Bayes
/
Diagnóstico por Computador
Tipo de estudo:
Diagnostic_studies
/
Health_economic_evaluation
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
J Med Syst
Ano de publicação:
1997
Tipo de documento:
Article
País de afiliação:
Eslovênia