AIMC Topic: Neural Networks, Computer

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Bump competition and lattice solutions in two-dimensional neural fields.

Neural networks : the official journal of the International Neural Network Society
Some forms of competition among activity bumps in a two-dimensional neural field are studied. First, threshold dynamics is included and rivalry evolutions are considered. The relations between parameters and dominance durations can match experimental...

Mapping quorum sensing onto neural networks to understand collective decision making in heterogeneous microbial communities.

Physical biology
Microbial communities frequently communicate via quorum sensing (QS), where cells produce, secrete, and respond to a threshold level of an autoinducer (AI) molecule, thereby modulating gene expression. However, the biology of QS remains incompletely ...

Application of machine learning in prediction of hydrotrope-enhanced solubilisation of indomethacin.

International journal of pharmaceutics
Systematic in-vitro studies have been conducted to determine the ability of a range of 10 potential hydrotropes to improve the apparent aqueous solubility of the poorly water soluble drug, indomethacin. Solubilisation of the drug in the presence of t...

Applying an artificial neural network model for developing a severity score for patients with hereditary amyloid polyneuropathy.

Amyloid : the international journal of experimental and clinical investigation : the official journal of the International Society of Amyloidosis
Hereditary (familial) amyloid polyneuropathy (FAP) is a systemic disease that includes a sensorimotor polyneuropathy related to transthyretin (TTR) mutations. So far, a scale designed to classify the severity of this disease has not yet been validate...

Detection and diagnosis of colitis on computed tomography using deep convolutional neural networks.

Medical physics
PURPOSE: Colitis refers to inflammation of the inner lining of the colon that is frequently associated with infection and allergic reactions. In this paper, we propose deep convolutional neural networks methods for lesion-level colitis detection and ...

Computerized detection of leukocytes in microscopic leukorrhea images.

Medical physics
PURPOSE: Detection of leukocytes is critical for the routine leukorrhea exam, which is widely used in gynecological examinations. An elevated vaginal leukocyte count in women with bacterial vaginosis is a strong predictor of vaginal or cervical infec...

A neural network approach for fast, automated quantification of DIR performance.

Medical physics
PURPOSE: A critical step in adaptive radiotherapy (ART) workflow is deformably registering the simulation CT with the daily or weekly volumetric imaging. Quantifying the deformable image registration accuracy under these circumstances is a complex ta...

Convolutional neural network-based encoding and decoding of visual object recognition in space and time.

NeuroImage
Representations learned by deep convolutional neural networks (CNNs) for object recognition are a widely investigated model of the processing hierarchy in the human visual system. Using functional magnetic resonance imaging, CNN representations of vi...

Dynamic response and transfer function of social systems: A neuro-inspired model of collective human activity patterns.

Neural networks : the official journal of the International Neural Network Society
The interaction of social networks with the external environment gives rise to non-stationary activity patterns reflecting the temporal structure and strength of exogenous influences that drive social dynamical processes far from an equilibrium state...

Deep Learning based Radiomics (DLR) and its usage in noninvasive IDH1 prediction for low grade glioma.

Scientific reports
Deep learning-based radiomics (DLR) was developed to extract deep information from multiple modalities of magnetic resonance (MR) images. The performance of DLR for predicting the mutation status of isocitrate dehydrogenase 1 (IDH1) was validated in ...