| D008959 |
Models, Neurological |
Theoretical representations that simulate the behavior or activity of the neurological system, processes or phenomena; includes the use of mathematical equations, computers, and other electronic equipment. |
Neurologic Models,Model, Neurological,Neurologic Model,Neurological Model,Neurological Models,Model, Neurologic,Models, Neurologic |
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| D011984 |
Sensory Receptor Cells |
Specialized afferent neurons capable of transducing sensory stimuli into NERVE IMPULSES to be transmitted to the CENTRAL NERVOUS SYSTEM. Sometimes sensory receptors for external stimuli are called exteroceptors; for internal stimuli are called interoceptors and proprioceptors. |
Nerve Endings, Sensory,Neurons, Sensory,Neuroreceptors,Receptors, Neural,Neural Receptors,Receptors, Sensory,Sensory Neurons,Sensory Receptors,Nerve Ending, Sensory,Neural Receptor,Neuron, Sensory,Neuroreceptor,Receptor Cell, Sensory,Receptor Cells, Sensory,Receptor, Neural,Receptor, Sensory,Sensory Nerve Ending,Sensory Nerve Endings,Sensory Neuron,Sensory Receptor,Sensory Receptor Cell |
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| D000465 |
Algorithms |
A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task. |
Algorithm |
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| D014795 |
Visual Pathways |
Set of cell bodies and nerve fibers conducting impulses from the eyes to the cerebral cortex. It includes the RETINA; OPTIC NERVE; optic tract; and geniculocalcarine tract. |
Pathway, Visual,Pathways, Visual,Visual Pathway |
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| D016000 |
Cluster Analysis |
A set of statistical methods used to group variables or observations into strongly inter-related subgroups. In epidemiology, it may be used to analyze a closely grouped series of events or cases of disease or other health-related phenomenon with well-defined distribution patterns in relation to time or place or both. |
Clustering,Analyses, Cluster,Analysis, Cluster,Cluster Analyses,Clusterings |
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| D016571 |
Neural Networks, Computer |
A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming. |
Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron |
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