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THE DECISION OF INTRAUTERINE GROWTH RETARDATION FROM ULTRASONOGRAPffiC EXAMINATIONS WITH NEURAL NETWORKS
| Content Provider | Semantic Scholar |
|---|---|
| Author | Giirgen, Fikret Onal, Emrah |
| Copyright Year | 2009 |
| Abstract | Our putpose is to make decision of intrauterine growth retardation (IUGR) through single and multiple ultrasonographic fetal growth assessments using a neural network (NN). This study was undertaken to show if a feedforward NN can learn nominal growth curves of head circumference (HC), abdominal circumference (AC), and HC/AC ratio versus gestational age and can help doctors in diagnosis ofIUGR Weekly (from 1 to 4 weeks) ultrasonographic examinations are taken as input to NN. A feedforward NN is used as a function approximator. Back propagation (BP) algorithm is used to optimize connection weights using samples from nominal curves. It was observed that a NN can improve the accuracy of the decision of IUGR by the multiple weekly examinations which mean monitoring the dynamic process of a change in size over time. It was concluded that the applicability of NNs to determination of IUGR is possible and it is a fruitfui line of inquiry for further work. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.mdpi.com/1300-686X/1/1/44/pdf |
| Alternate Webpage(s) | http://www.mdpi.com/2297-8747/1/1/44/pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Abdominal Circumference Artificial neural network Back Pain Backpropagation Biological Neural Networks Feed forward (control) Feedforward neural network Fetal Growth Retardation Head circumference Intrauterine Medical ultrasound NN304 Software propagation Weight algorithm |
| Content Type | Text |
| Resource Type | Article |
