Improving the efficacy of automated fetal state assessment with fuzzy analysis of delivery outcome

• Autorzy: Czabanski R. , Jezewski M. , Horoba K. , Jezewski J. , Leski J.
• Języki publikacji: EN

Abstrakty

EN

A number of methods of the qualitative assessment of fetal heart rate (FHR) signals are based on supervised learning. The classification methods based on the supervised learning require a set of training recordings accompanied by the reference interpretation. In the real data collections the class of signals related to fetal distress is usually under-represented. Too small percentage of distress patterns adversely affects the effectiveness of the automated evaluation of the fetal state. The paper presents a method of equalizing the class sizes based on the reference assessment of the fetal state with the fuzzy analysis of the newborn attributes. The supervised learning with increased number of the FHR signals, which are characterized by the highest rate of the fuzzy inference leads to significant increase of the efficacy of the qualitative assessment of the fetal state using the Lagrangian support vector machine.

Słowa kluczowe

EN

fetal monitoring; fuzzy inference; support vector machine; supervised learning

PL

monitorowanie płodu; wnioskowanie rozmyte; maszyna wektorów nośnych; uczenie nadzorowane

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2015
• Tom: Vol. 24
• Strony: 223--230
• Opis fizyczny: Bibliogr. 26 poz., tab., wykr.

Twórcy

autor

Czabanski R.

• Silesian University of Technology, Institute of Electronics, Akademicka Str. 16, 44-100 Gliwice, Poland

autor

Jezewski M.

• Silesian University of Technology, Institute of Electronics, Akademicka Str. 16, 44-100 Gliwice, Poland

autor

Horoba K.

• Institute of Medical Technology and Equipment ITAM, Roosevelt Str. 118, 41-800 Zabrze, Poland

autor

Jezewski J.

• Institute of Medical Technology and Equipment ITAM, Roosevelt Str. 118, 41-800 Zabrze, Poland

autor

Leski J.

• Silesian University of Technology, Institute of Electronics, Akademicka Str. 16, 44-100 Gliwice, Poland

Bibliografia

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