Cargando…
Determination of Fetal State from Cardiotocogram Using LS-SVM with Particle Swarm Optimization and Binary Decision Tree
We use least squares support vector machine (LS-SVM) utilizing a binary decision tree for classification of cardiotocogram to determine the fetal state. The parameters of LS-SVM are optimized by particle swarm optimization. The robustness of the method is examined by running 10-fold cross-validation...
Autores principales: | Yılmaz, Ersen, Kılıkçıer, Çağlar |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3830816/ https://www.ncbi.nlm.nih.gov/pubmed/24288574 http://dx.doi.org/10.1155/2013/487179 |
Ejemplares similares
-
An Expert System Based on Fisher Score and LS-SVM for Cardiac Arrhythmia Diagnosis
por: Yılmaz, Ersen
Publicado: (2013) -
Binary particle swarm optimization for operon prediction
por: Chuang, Li-Yeh, et al.
Publicado: (2010) -
Binary Restructuring Particle Swarm Optimization and Its Application
por: Zhu, Jian, et al.
Publicado: (2023) -
High-Quality Transmission of Cardiotocogram and Fetal Information Using a 5G System: Pilot Experiment
por: Naruse, Katsuhiko, et al.
Publicado: (2020) -
Detection of Preventable Fetal Distress During Labor From Scanned Cardiotocogram Tracings Using Deep Learning
por: Frasch, Martin G., et al.
Publicado: (2021)