Artificial neural networks are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the efficiency of a neural network for predicting the survival of patients with acute pancreatitis is compared with days-of-survival obtained from patients. A three- layer back-propagation neural network was developed for this purpose. Clinical data (e.g...

â â â â â â â  this paper proposes a new forecasting model for investigating relationship between the price of crude oil, as an important energy source and gdp of the us, as the largest oil consumer, and the uk, as the oil producer. gmdh neural network and mlff neural network approaches, which are both non-linear models, are employed to forecast gdp responses to the oil price changes. the resul...

modelling and forecasting stock market is a challenging task for economists and engineers since it has a dynamic structure and nonlinear characteristic. this nonlinearity affects the efficiency of the price characteristics. using an artificial neural network (ann) is a proper way to model this nonlinearity and it has been used successfully in one-step-ahead and multi-step-ahead prediction of di...

bedload transport is an essential component of river dynamics and estimation of its rate is important to many aspects of river management. in this study, measured bedload by helley- smith sampler was used to estimate the bedload transport of kurau river in malaysia. an artificial neural network, genetic programming and a combination of genetic programming and a neural network were used to estim...

This article contrives a neural-adaptive constrained controller of the cable towed air–ground recovery system subject to terrain obstacles, unmeasurable tensions, trailing vortex, wind gust, and actuator saturation. In modeling, vehicle's nominal 6 DOF affine nonlinear dynamics system's finite links-joints are formulated. To achieve accurate under an asymmetric barrier Lyapunov function-based f...

Despite multiple sexual exposure to HIV-1 virus, some individuals remain HIV-1 seronegative (exposed seronegative, ESN). The mechanisms underlying this resistance remain still unclear, although a multifactorial pathogenesis can be hypothesised. Although several genetic factors have been related to HIV-1 resistance, the homozigosity for a mutation in CCR5 gene (the 32 bp deletion, i.e. CCR5-Delt...

We propose an integer approximation of Echo State Networks (ESN) based on the mathematics of hyperdimensional computing. The reservoir of the proposed Integer Echo State Network (intESN) contains only n-bits integers and replaces the recurrent matrix multiply with an efficient cyclic shift operation. Such an architecture results in dramatic improvements in memory footprint and computational eff...

The proposed IAFC neural networks have both stability and plasticity because theyuse a control structure similar to that of the ART-1(Adaptive Resonance Theory) neural network.The unsupervised IAFC neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. This fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. The supervised IAFC ...

OBJECTIVE To determine the rate of distal symmetrical polyneuropathy (DSP) in patients with type 2 diabetes mellitus, to evaluate the role of history, neurological examination and the electrodiagnostic methods in the diagnosis of DSP, and to determine the association between electromyography-supported neuropathy (ESN), neuropathic complaints (NCs) and risk factors. SUBJECTS AND METHODS A tota...

Preoperative differentiation of benign endometrial stromal nodule (ESN) from malignant low-grade endometrial sarcoma (LGESS) is challenging, because it requires histological evaluation of the tumor-myometrium interface, which is difficult to obtain in conventional endometrial curettage. A 72-year-old postmenopausal woman presented with 5-year history of persistent vaginal bleeding. Histological...