Feature Selection for Classification Incorporating Less Meaningful Attributes in Medical Diagnostics

• Autorzy: Agnieszka Wosiak , Danuta Zakrzewska
• Języki publikacji: EN

Abstrakty

EN

In medical diagnostics there is a constant need of searching for new methods of attribute acquiring, but it is difficult to asses if these new features can support the existing ones and can be useful in medical inference. In the paper the methodology of discovering features which are less informative while considering independently, however meaningful for diagnosis making, is investigated. The proposed methodology can contribute to the better use of attributes, which has not been considered in the diagnostics process so far. The experimental study, which concerns arterial hypertension as one of the civilization diseases demanding early detection and improved treatment is presented. The experiments confirmed that additional attributes enable obtaining the diagnostic results comparable to the ones received by using the most obvious features.(original abstract)

Słowa kluczowe

EN

Medicine; Diagnostic method; Medical experiments

PL

Medycyna; Metody diagnostyczne; Eksperymenty medyczne

• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2014
• Tom: 2
• Strony: 235--240

Twórcy

autor

Agnieszka Wosiak

• Lodz University of Technology, Poland

autor

Danuta Zakrzewska

• Lodz University of Technology, Poland

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