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Predicting the risk of metabolic acidosis for newborns based on fetal heart rate signal classification using support vector machines.
George K. Georgoulas
Chrysostomos D. Stylios
Petros P. Groumpos
Published in:
IEEE Trans. Biomed. Eng. (2006)
Keyphrases
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heart rate
classification using support vector machines
blood pressure
heart rate variability
multiresolution
support vector machine
physical activity
physiological signals
vital signs
risk management
risk assessment
risk factors
ecg signals
decision making
data sets
data mining