AIMC Topic: Neural Networks, Computer

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Quantitative structure-retention relationship model for the determination of naratriptan hydrochloride and its impurities based on artificial neural networks coupled with genetic algorithm.

Talanta
Mathematical modeling of Quantitative Structure - Property Relationships met great interest in fields of in silico drug design and more recently, pharmaceutical analysis. In our approach we proposed automated method of creation Quantitative Structure...

Artificial Neural Networks approach to pharmacokinetic model selection in DCE-MRI studies.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: In pharmacokinetic analysis of Dynamic Contrast Enhanced MRI data, a descriptive physiological model should be selected properly out of a set of candidate models. Classical techniques suggested for this purpose suffer from issues like comput...

Modeling the N400 ERP component as transient semantic over-activation within a neural network model of word comprehension.

Cognition
The study of the N400 event-related brain potential has provided fundamental insights into the nature of real-time comprehension processes, and its amplitude is modulated by a wide variety of stimulus and context factors. It is generally thought to r...

Investigation of co-combustion characteristics of sewage sludge and coffee grounds mixtures using thermogravimetric analysis coupled to artificial neural networks modeling.

Bioresource technology
Artificial neural network (ANN) modeling was applied to thermal data obtained by non-isothermal thermogravimetric analysis (TGA) from room temperature to 1000°C at three different heating rates in air to predict the TG curves of sewage sludge (SS) an...

Development of pharmacophore-based classification model for activators of constitutive androstane receptor.

Drug metabolism and pharmacokinetics
Constitutive androstane receptor (CAR) is predominantly expressed in the liver and is important for regulating drug metabolism and transport. Despite its biological importance, there have been few attempts to develop in silico models to predict the a...

An artificial neural network method for lumen and media-adventitia border detection in IVUS.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Intravascular ultrasound (IVUS) has been well recognized as one powerful imaging technique to evaluate the stenosis inside the coronary arteries. The detection of lumen border and media-adventitia (MA) border in IVUS images is the key procedure to de...

Adaptive exponential synchronization of complex-valued Cohen-Grossberg neural networks with known and unknown parameters.

Neural networks : the official journal of the International Neural Network Society
The complex-valued Cohen-Grossberg neural network is a special kind of complex-valued neural network. In this paper, the synchronization problem of a class of complex-valued Cohen-Grossberg neural networks with known and unknown parameters is investi...

Classification of Parkinson's disease utilizing multi-edit nearest-neighbor and ensemble learning algorithms with speech samples.

Biomedical engineering online
BACKGROUND: The use of speech based data in the classification of Parkinson disease (PD) has been shown to provide an effect, non-invasive mode of classification in recent years. Thus, there has been an increased interest in speech pattern analysis m...

Reachable Set Estimation for Markovian Jump Neural Networks With Time-Varying Delays.

IEEE transactions on cybernetics
In this paper, the reachable set estimation problem is investigated for Markovian jump neural networks (NNs) with time-varying delays and bounded peak disturbances. Our goal is to find a set as small as possible which bounds all the state trajectorie...

Segmentation of Fetal Left Ventricle in Echocardiographic Sequences Based on Dynamic Convolutional Neural Networks.

IEEE transactions on bio-medical engineering
Segmentation of fetal left ventricle (LV) in echocardiographic sequences is important for further quantitative analysis of fetal cardiac function. However, image gross inhomogeneities and fetal random movements make the segmentation a challenging pro...