AIMC Topic: Neural Networks, Computer

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Local distinguishability aggrandizing network for human anomaly detection.

Neural networks : the official journal of the International Neural Network Society
With the growing demand for an intelligent system to prevent abnormal events, many methods have been proposed to detect and locate anomalous behaviors in surveillance videos. However, most of these methods contain two shortcomings mainly: distraction...

A review on neural network models of schizophrenia and autism spectrum disorder.

Neural networks : the official journal of the International Neural Network Society
This survey presents the most relevant neural network models of autism spectrum disorder and schizophrenia, from the first connectionist models to recent deep neural network architectures. We analyzed and compared the most representative symptoms wit...

Using multi-layer perceptron with Laplacian edge detector for bladder cancer diagnosis.

Artificial intelligence in medicine
In this paper, the urinary bladder cancer diagnostic method which is based on Multi-Layer Perceptron and Laplacian edge detector is presented. The aim of this paper is to investigate the implementation possibility of a simpler method (Multi-Layer Per...

Automated detection of focal cortical dysplasia using a deep convolutional neural network.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Focal cortical dysplasia (FCD) is one of the commonest epileptogenic lesions, and is related to malformations of the cortical development. The findings on magnetic resonance (MR) images are important for the diagnosis and surgical planning of FCD. In...

Reducing variability in motor cortex activity at a resting state by extracellular GABA for reliable perceptual decision-making.

Journal of computational neuroscience
Interaction between sensory and motor cortices is crucial for perceptual decision-making, in which intracortical inhibition might have an important role. We simulated a neural network model consisting of a sensory network (N) and a motor network (N) ...

Prediction mapping of human leptospirosis using ANN, GWR, SVM and GLM approaches.

BMC infectious diseases
BACKGROUND: Recent reports of the National Ministry of Health and Treatment of Iran (NMHT) show that Gilan has a higher annual incidence rate of leptospirosis than other provinces across the country. Despite several efforts of the government and NMHT...

Development of artificial neural network model for prediction of post-streptococcus mutans in dental caries.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Streptococcus mutans is the primary initiator and most common organism associated with dental caries. Prediction of post-Streptococcus mutans favours in the selection of appropriate caries excavation method which eventually ...

Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs.

Radiology
Background Multicenter studies are required to validate the added benefit of using deep convolutional neural network (DCNN) software for detecting malignant pulmonary nodules on chest radiographs. Purpose To compare the performance of radiologists in...