Predicting High-Risk Preterm Birth Using Artificial Neural Networks.

Predicting High-Risk Preterm Birth Using Artificial Neural Networks.

A reengineered approach to the early prediction of preterm birth is presented as a complimentary technique to the current procedure of using costly and invasive clinical testing on high-risk maternal populations. Artificial neural networks (ANNs) are employed as a screening tool for preterm birth on...

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Publié dans:IEEE Transactions on information technology in biomedicine 10, 3 (2006).
Auteur principal: Catley, C.
Format: Article
Langue:English
Sujets:
Artificial neural networks.
Artificial training set.
Back-propagation feedforward ANN.
Decision support systems.
Free flow oxygen.
Gestation.
Heterogeneous maternal population.
Network sensitivity.
Obstetrical outcome estimation.
Pattern classification.
Perinatal care.
Preterm birth prediction.
Reengineered approach.
Refined high-risk preterm birth outcome.
Resuscitation.
Risk estimation.