AIMC Topic: Neural Networks, Computer

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Artificial neural network approach for predicting blood brain barrier permeability based on a group contribution method.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The purpose of this study was to develop a quantitative structure-activity relationship (QSAR) model for the prediction of blood brain barrier (BBB) permeability by using artificial neural networks (ANN) in combination with ...

Traffic accident detection and condition analysis based on social networking data.

Accident; analysis and prevention
Accurate detection of traffic accidents as well as condition analysis are essential to effectively restoring traffic flow and reducing serious injuries and fatalities. This goal can be obtained using an advanced data classification model with a rich ...

A survey of deep learning models in medical therapeutic areas.

Artificial intelligence in medicine
Artificial intelligence is a broad field that comprises a wide range of techniques, where deep learning is presently the one with the most impact. Moreover, the medical field is an area where data both complex and massive and the importance of the de...

Intermittent Control for Quasisynchronization of Delayed Discrete-Time Neural Networks.

IEEE transactions on cybernetics
This article visits the intermittent quasisynchronization control of delayed discrete-time neural networks (DNNs). First, an event-dependent intermittent mechanism is originally designed, which is described by the Lyapunov function and three non-nega...

Exponential Stabilization of Inertial Memristive Neural Networks With Multiple Time Delays.

IEEE transactions on cybernetics
This article investigates the global exponential stabilization (GES) of inertial memristive neural networks with discrete and distributed time-varying delays (DIMNNs). By introducing the inertial term into memristive neural networks (MNNs), DIMNNs ar...

Synchronization of Nonidentical Neural Networks With Unknown Parameters and Diffusion Effects via Robust Adaptive Control Techniques.

IEEE transactions on cybernetics
This paper considers the self-synchronization and tracking synchronization issues for a class of nonidentically coupled neural networks model with unknown parameters and diffusion effects. Using the special structure of neural networks with global Li...

Construction and Supervised Learning of Long-Term Grey Cognitive Networks.

IEEE transactions on cybernetics
Modeling a real-world system by means of a neural model involves numerous challenges that range from formulating transparent knowledge representations to obtaining reliable simulation errors. However, that knowledge is often difficult to formalize in...

Automatic Construction of Chinese Herbal Prescriptions From Tongue Images Using CNNs and Auxiliary Latent Therapy Topics.

IEEE transactions on cybernetics
The tongue image provides important physical information of humans. It is of great importance for diagnoses and treatments in clinical medicine. Herbal prescriptions are simple, noninvasive, and have low side effects. Thus, they are widely applied in...

Application of Machine-Learning Methods to Recognize mitoBK Channels from Different Cell Types Based on the Experimental Patch-Clamp Results.

International journal of molecular sciences
(1) Background: In this work, we focus on the activity of large-conductance voltage- and Ca2+-activated potassium channels (BK) from the inner mitochondrial membrane (mitoBK). The characteristic electrophysiological features of the mitoBK channels ar...

The Feature Ambiguity Mitigate Operator model helps improve bone fracture detection on X-ray radiograph.

Scientific reports
This study was performed to propose a method, the Feature Ambiguity Mitigate Operator (FAMO) model, to mitigate feature ambiguity in bone fracture detection on radiographs of various body parts. A total of 9040 radiographic studies were extracted. Th...