The aim of the present study was to design, implement, and evaluate a software system for discriminating between metastases, meningiomas, and gliomas on MRI. The proposed classifier is a modified probabilistic neural network (PNN), incorporating a second degree least squares features transformation (LSFT) into the PNN classifier. Thirty-six textural features were extracted from each one of 75 T...

The perineuronal net (PNN) represents a lattice-like structure that is prominently expressed along the soma and proximal dendrites of parvalbumin- (PV-) positive interneurons in varied brain regions including the cortex and hippocampus. It is thus apposed to sites at which PV neurons receive synaptic input. Emerging evidence suggests that changes in PNN integrity may affect glutamatergic input ...

This article deals with the problem of determination of the model uncertainty during the system identification via application of the self-organising group method of data handling (GMDH) neural network. In particular, the contribution of the neural network structure errors and the parameter estimates inaccuracy to the model uncertainty were presented. Knowing these sources and applying the Oute...

Previous studies have implemented Backpropagation Feedforward Neural Networks (BPNNs) as an alternative technique to Linear Discriminant Analysis (LDA) to predict bond ratings using relatively small data sets due to the limited number of bond ratings data available. Although these studies report the superiority of BPNNs over the LDA to predict bond ratings, they seem to ignore that BPNNs suffer...

To accurately and reliably predict the occurrence of rockburst disasters, a intensity level prediction model based on FA-SSA-PNN is proposed. Crding to internal external factors occurrence, six influencing (σθ, σt, σc, σc/σt, σθ/σc, Wet) were selected build index system. Seventy-five sets typical case data at home abroad collected, original preprocessed factor analysis (FA), comprehensive index...

The planning of an adequate nutritional support for meeting the metabolic requirements of sick neonates is a tedious time consuming calculation, needs practical expert knowledge and involves the risk of introducing possibly fatal errors. We therefore developed the interactive support system VIE–PNN for calculating the composition of parenteral nutrition solutions (PNS) for neonates at intensive...

Item ranking and selection plays a key role in constructing concise and informative educational tests. Traditional techniques based on the item response theory (IRT) have been used to automate this task, but they require model parameters to be determined a priori of each item and their application becomes more tedious with larger item banks. Machine learning techniques can be used to build data...

Abstract Weirs are one of the most common hydraulic structures used in water engineering projects. In this research, a group method data handling (GMDH) was developed to estimate energy dissipation flow passing over labyrinth weirs with triangular and trapezoidal plans. To compare performance model other types soft computing models, multilayer perceptron neural network (MLPNN) developed. The di...

Chondroitin sulfate proteoglycans (CSPGs) are major components of the extracellular matrix (ECM) in the brain. In adult mammals, CSPGs form the specialized ECM structure perineuronal nets (PNNs) that surround somata and dendrites of certain types of neurons. PNNs restrict synaptic plasticity and regulate the closure of critical periods. Although previous studies have examined the starting perio...