Temat: fuzzy classification - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Fuzzy system for evaluation of fetal heart rate signals using FIGO criteria
Autorzy:: Czabański, R.
Jeżewski, M.
Wróbel, J.
Jeżewski, J.
Horoba, K.
Powiązania:: https://bibliotekanauki.pl/articles/333142.pdf
Data publikacji:: 2009
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: monitoring płodu
tętno płodu
kryteria FIGO
fetal monitoring
fetal heart rate
signal classification
fuzzy systems
Opis:: Cardiotocography is a biophysical method of fetal monitoring during pregnancy and labour. It is mainly based on recording and analysis of fetal heart activity. The computerized fetal monitoring systems provide the quantitative description of the recorded signals but the effective methods supporting the conclusion generation are still needed. The evaluation of the signal can be made using criteria recommended by FIGO. Nevertheless, the quantitative description of the traces is inconsistent with qualitative nature of the obstetric knowledge. Therefore, we applied the fuzzy system based on Takagi-Sugeno-Kang model to evaluate and classify signals. FIGO guidelines were used for developing a set of fuzzy conditional rules defining the system performance. The proposed system was evaluated using data collected with computerized fetal surveillance system – MONAKO. The classification results confirm the improvement of the fetal state evaluation quality while using the proposed fuzzy system support.
Źródło:: Journal of Medical Informatics & Technologies; 2009, 13; 189-194
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Fuzzy prediction of fetal acidemia
Autorzy:: Czabański, R.
Roj, D.
Jeżewski, J.
Horoba, K.
Jeżewski, M.
Powiązania:: https://bibliotekanauki.pl/articles/333483.pdf
Data publikacji:: 2011
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: monitorowanie płodu
tętno płodu
klasyfikacja sygnału
systemy rozmyte
fetal monitoring
fetal heart rate
signal classification
fuzzy systems
Opis:: Cardiotocography is the primary method for biophysical assessment of a fetal state. It is based mainly on the recording and analysis of fetal heart rate signal (FHR). Computer systems for fetal monitoring provide a quantitative description of FHR signals, however the effective methods for their qualitative assessment are still needed. The measurements of hydronium ions concentration (pH) in newborn cord blood is considered as the objective indicator of the fetal state. Improper pH level is a symptom of acidemia being the result of fetal hypoxia. The paper proposes a twostep analysis of signals allowing for effective prediction of the acidemia risk. The first step consists in the fuzzy classification of FHR signals. The task of fuzzy inference is to indicate signals that according to the FIGO guidelines represent the fetal wellbeing. These recordings are eliminated from the further classification with Lagrangian Support Vector Machines. The proposed procedure was evaluated using data collected with computerized fetal surveillance system. The classification results confirmed the high quality of the proposed fuzzy method of fetal state evaluation.
Źródło:: Journal of Medical Informatics & Technologies; 2011, 17; 81-87
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Unsupervised clustering for fetal state assessment based on selected features of the cardiotocographic signals
Autorzy:: Przybyła, T.
Jeżewski, J.
Roj, D.
Powiązania:: https://bibliotekanauki.pl/articles/333112.pdf
Data publikacji:: 2009
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: klasyfikacja algorytmów bez nadzoru
grupowanie danych
monitoring płodu
kardiotokografia
unsupervised classification
fuzzy clustering
principal component analysis
fetal monitoring
Opis:: In modern obstetrics the cardiotocography is a routine method of fetal condition assessment based mainly on analysis of the fetal heart rate signals. The correct interpretation of recorded 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 techniques enabling automated conclusion generation based on cardiotocograms are still being searched. The paper presents an attempt to diagnose the fetal state basing on seventeen features describing the cardiotocographic records. The proposed method applies the unsupervised classification of signals. During our research we tried to classify the fetal state using the fuzzy c-means (FCM) clustering. We also tested how the efficiency of classification could be influenced by application of principal component analysis (PCA) algorithm. The obtained results showed that unsupervised classification cannot be considered as a support to fetal state assessment.
Źródło:: Journal of Medical Informatics & Technologies; 2009, 13; 157-162
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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