Usage of naive Bayes classifier in decision module of e-learning decision support system

• Autorzy: Chabior M. , Noga A. , Tkacz M.
• Języki publikacji: EN

Abstrakty

EN

This article describes adopted, within the scope of one of e-leaming system creation, a method of diagnosis generation based on defined symptoms with the use of the Bayes naive algorithm. It is intended for Medical Faculties students, inference module shall facilitate determination of probability of the influence of individual symptoms on diagnosis. Practical application of such approach presented in the article gives the possibility of distant verification of student's knowledge taking into account not only diagnosis, but also will facilitate gaining skills of appearance materiality determination of symptoms in relation to diagnosed affection. For the testing purposes of adopted assumptions the hundred element database has been applied depending on spine affection in discopathy form and factors, which can affect the origin of the affection - obesity and hard physical work. The operation of the Bayes algorithm has been presented within the scope of influence evaluation of enumerated factors on affection origin.

Słowa kluczowe

EN

Bayesian network; naive Bayes estimation; elearning; decision support systems; medical e-diagnosis

• Wydawca: Uniwersytet Jagielloński - Collegium Medicum ; Index Copernicus Sp. z o.o.
• Czasopismo: Bio-Algorithms and Med-Systems
• Rocznik: 2009
• Tom: Vol. 5, no. 10
• Strony: 31--34
• Opis fizyczny: Bibliogr. 7 poz., tab.

Twórcy

autor

Chabior M.

• University of Silesia Faculty of Computer and Materials Science Institute of Computer Science

autor

Noga A.

• University of Silesia Faculty of Computer and Materials Science Institute of Computer Science

autor

Tkacz M.

• University of Silesia Faculty of Computer and Materials Science Institute of Computer Science

Bibliografia

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• 9. Hand D., Mannila H., Smyth P.: Principles of Data Mining, Massachusets Institute of Technology, Cambridge 2001.
• 10. Friedman N., Linial M., Nachman I., Peer D.: Using Bayesian Networks to Analyze Expression Data, Hebrew University, J. Computational Biology, Vol. 7, No. 3-4, pp. 601-620, 2000. Kwiatkowska A. M.: Systemy wspomagania decyzji, Wydawnictwo Naukowe PWN, Warszawa 2007.