Adaptive Pattern Recognition in The Analysis of Cardiotocographic Recods  

Oleh:

Fontenla-Romero, O. ; Alonso-Betanzos, A. ; Guijarro-Berdinas, B.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 12 no. 5 (2001), page 1188-1195.
Topik: recognition; pattern recognition; cardiotocographic; records

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.5 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

The recognition of accelerative and decelerative patterns in the fetal heart rate (FHR) is one of the tasks carried out manually by obstetricians when they analyze cardiotocograms for information respecting the fetal state. An approach based on artificial neural networks formed by a multilayer perceptron (MLP) is developed. However, since the system utilizes the FHR signal as direct input, an anterior stage must be incorporated that applies a principal component analysis (PCA) so as to make the system independent of the signal baseline. Furthermore, the introduction of multiresolution into the PCA has resolved other problems that were detected in the application of the system. Presented in this paper are the results of validation of these systems designated the PCA - MLP and multi resolution principal component analysis (MR - PCA) systems against three clinical experts.

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