MeSH Browser

MeSH Heading: Neural Networks, Computer
Tree Number(s): G17.485; L01.224.050.375.605
Unique ID: D016571
RDF Unique Identifier: http://id.nlm.nih.gov/mesh/D016571
Annotation: do not confuse with NEURAL NETWORKS (ANATOMIC) see NERVE NET
Scope Note: 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.
Entry Term(s): Computational Neural Networks; Connectionist Models; Models, Neural Network; Neural Network Models; Neural Networks (Computer); Perceptrons
Previous Indexing: Artificial Intelligence (1987-1991); Computer Simulation (1987-1991); Image Processing, Computer-Assisted (1990-1991)
Public MeSH Note: 2020; was NEURAL NETWORKS (COMPUTER) 1992-2019
History Note: 2020 (1992); was NEURAL NETWORKS (COMPUTER) 1992-2019
Date Established: 1992/01/01
Date of Entry: 1991/01/25
Revision Date: 2019/01/18

No Qualifiers

Mathematical Concepts [G17]

Information Science [L01]
- Computing Methodologies [L01.224]
  - Algorithms [L01.224.050]
    - Artificial Intelligence [L01.224.050.375]

Neural Networks, Computer Preferred

Concept UI: M0025278
Scope Note: 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.
Terms: Neural Networks, Computer Preferred Term
Term UI T000950585
Date01/18/2019
LexicalTag NON
ThesaurusID NLM (2020); Models, Neural Network
Term UI T049573
Date11/28/1990
LexicalTag NON
ThesaurusID NLM (1992); Neural Network Models
Term UI T049574
Date10/09/1990
LexicalTag NON
ThesaurusID NLM (1992); Connectionist Models
Term UI T049572
Date12/19/1990
LexicalTag NON
ThesaurusID NLM (1992); Perceptrons
Term UI T049576
Date10/09/1990
LexicalTag NON
ThesaurusID NLM (1992); Computational Neural Networks
Term UI T000950586
Date01/18/2019
LexicalTag NON
ThesaurusID NLM (2020); Neural Networks (Computer)
Term UI T049575
Date01/01/1999
LexicalTag NON
ThesaurusID NLM (1992)

Neural Networks, Computer MeSH Descriptor Data 2024