Linked Life Data

8222616

Source:http://linkedlifedata.com/resource/pubmed/id/8222616

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
1993-12-16
pubmed:abstractText
A feature extractor for determining the latency of peak V in brainstem auditory evoked potentials (BAEPs) is presented in this paper. A feature extractor that combines artificial neural networks with an algorithmic approach is presented. It consists of a series of small neural networks that have to make simple decisions. Each neural network decides what part of the input pattern contains the peak, and the algorithm passes that part of the pattern to the next neural network; in this way the size of the input patterns decreases during the process, and the last neural network determines the exact location of the peak. An optimal configuration of neural networks could determine the latencies of peak V in all synthetic evoked potentials correctly. With real evoked potentials, the networks yield results that comply with the opinion of a human expert in 80 +/- 6% of the cases.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0010-4825
pubmed:author
pubmed:issnType
Print
pubmed:volume
23
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
369-80
pubmed:dateRevised
2004-11-17
pubmed:meshHeading
pubmed:year
1993
pubmed:articleTitle
Identification of peak V in brainstem auditory evoked potentials with neural networks.
pubmed:affiliation
Division of Medical Electrical Engineering, Eindhoven University of Technology, The Netherlands.
pubmed:publicationType
Journal Article