About the paper
| Title |
Diagnosis of Lumbar Disc Herniation using Multilayer Perceptron Neural Network |
| Book |
ICIST 2015 Proceedings |
| Pages |
210-213 |
| Abstract: The aim of this study was to develop multilayer
perceptron (MLP) neural network model to predict lumbar
disc herniation. The age, gender, body mass index, the
maximum displacement of the body center of force, left foot
center of force, right foot center of force in the x and y
directions have been used as the input variables for the
established MLP model. The measurements were performed
using the commercial software Foot Work Pro. A total of 40
patients have been divided into training and testing data
sets. The study results suggested that MLP would be an
efficient soft computing tool for diagnosis of lumbar disc
herniation. The Pearson coefficients have been computed as
0.941 and 0.938 for training and test data sets, respectively. |
Full citation
Milanković, I.,
Ranković, V.,
Peulić, M.,
Filipović, N.,
Peulić, A.
Diagnosis of Lumbar Disc Herniation using Multilayer Perceptron Neural Network. In:
Zdravković, M.,
Trajanović, M.,
Konjović, Z.
(Eds.)
ICIST 2015 Proceedings, pp.210-213, 2015
Keywords
Healthcare and medicine
Neural networks
Machine learning