The prediction of the low fetal birth weight based on quantitative description of cardiotocographic signals

• Autorzy: Czabański R. , Jeżewski M. , Wróbel J. , Kupka T. , Łęski J. , Jeżewski J.
• Języki publikacji: EN

Abstrakty

EN

Cardiotocography (CTG) is a routine method of fetal condition assessment used in modern obstetrics. It is a biophysical method based on simultaneous recording and analysis of activity of fetal heart, fetal movements and maternal uterine contractions. The fetal condition is diagnosed on the basis of printed CTG trace evaluation. The correct interpretation of CTG traces from a bedside monitor is very difficult even for experienced clinicians. Therefore, computerized fetal monitoring systems are used to yield the quantitative description of the signal. However, the effective methods, aiming to support the conclusion generation, are still being searched. One of the most important features defining the state of fetal outcome is the weight of the newborn. The presented work describes an application of the Artificial Neural Network Based on Logical Interpretation of fuzzy if-then Rules (ANBLIR) to evaluate the risk of the low birth weight using a set of parameters quantitatively describing the CTG traces. The obtained results confirm that the neuro-fuzzy based CTG classification methods are very efficient for the prediction of the fetal outcome.

Słowa kluczowe

EN

online signature verification; feature context; dynamic programming

PL

weryfikacja podpisu online; programowanie dynamiczne

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2008
• Tom: Vol. 12
• Strony: 97--102
• Opis fizyczny: Bibliogr. 11 poz., rys., tab.

Twórcy

autor

Czabański R.

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

autor

Jeżewski M.

autor

Wróbel J.

autor

Kupka T.

autor

Łęski J.

autor

Jeżewski J.

Bibliografia

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