AIMC Topic: Neural Networks, Computer

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Identifying the Basal Ganglia network model markers for medication-induced impulsivity in Parkinson's disease patients.

PloS one
Impulsivity, i.e. irresistibility in the execution of actions, may be prominent in Parkinson's disease (PD) patients who are treated with dopamine precursors or dopamine receptor agonists. In this study, we combine clinical investigations with comput...

Synchronization of Memristor-Based Coupling Recurrent Neural Networks With Time-Varying Delays and Impulses.

IEEE transactions on neural networks and learning systems
Synchronization of an array of linearly coupled memristor-based recurrent neural networks with impulses and time-varying delays is investigated in this brief. Based on the Lyapunov function method, an extended Halanay differential inequality and a ne...

Joint Toxicity of Lead, Chromium, Cobalt and Nickel to Photobacterium phosphoreum at No Observed Effect Concentration.

Bulletin of environmental contamination and toxicology
Joint toxicity of Pb2+, Cr3+, Co2+ and Ni2+ toward Photobacterium phosphoreum (Ph. phosphoreum) at the no observed effect concentration (NOEC) was determined through a factorial experiment. A neural network model was designed according to experimenta...

The rate of mucosal healing by azathioprine therapy and prediction by artificial systems.

The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology
BACKGROUND/AIMS: We aimed to assess the effect of azathioprine on mucosal healing in patients with inflammatory bowel diseases (IBD). Artificial neural networks were applied to IBD data for predicting mucosal remission.

Differential diagnosis of pleural mesothelioma using Logic Learning Machine.

BMC bioinformatics
BACKGROUND: Tumour markers are standard tools for the differential diagnosis of cancer. However, the occurrence of nonspecific symptoms and different malignancies involving the same cancer site may lead to a high proportion of misclassifications. Cla...

Teaching a Machine to Feel Postoperative Pain: Combining High-Dimensional Clinical Data with Machine Learning Algorithms to Forecast Acute Postoperative Pain.

Pain medicine (Malden, Mass.)
BACKGROUND: Given their ability to process highly dimensional datasets with hundreds of variables, machine learning algorithms may offer one solution to the vexing challenge of predicting postoperative pain.

Prostate cancer identification: quantitative analysis of T2-weighted MR images based on a back propagation artificial neural network model.

Science China. Life sciences
Computer-aided diagnosis (CAD) systems have been proposed to assist radiologists in making diagnostic decisions by providing helpful information. As one of the most important sequences in prostate magnetic resonance imaging (MRI), image features from...

Improving nonlinear modeling capabilities of functional link adaptive filters.

Neural networks : the official journal of the International Neural Network Society
The functional link adaptive filter (FLAF) represents an effective solution for online nonlinear modeling problems. In this paper, we take into account a FLAF-based architecture, which separates the adaptation of linear and nonlinear elements, and we...

Convergence analysis of an augmented algorithm for fully complex-valued neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper presents an augmented algorithm for fully complex-valued neural network based on Wirtinger calculus, which simplifies the derivation of the algorithm and eliminates the Schwarz symmetry restriction on the activation functions. A unified me...