Self-Organizing Maps as Data Classifier in Medical Applications

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00191146" target="_blank" >RIV/68407700:21230/11:00191146 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.ncta.ijcci.org" target="_blank" >http://www.ncta.ijcci.org</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Self-Organizing Maps as Data Classifier in Medical Applications

Popis výsledku v původním jazyce

Many researchers use mathematical-engineering methods in different domains of life, and medical research is no exception. One area for application of such methods is to assist people with different forms of disabilities. The methods described in the following text are oriented towards the analysis of disordered children's speech with the diagnosis of Specific Language Impairment (SLI), also named as Developmental Dysphasia (DD), and the analysis of the expressive speech. Both methods make use of KohonenSelf-Organizing Maps (KSOM) or Supervised Self-Organizing Maps (SSOM) for the analysis and the classification of features from utterances of healthy and ill children, or adult speakers for emotions analysis. The possibility of cluster visualisation is used for monitoring of disorder trends and therapy success. These experiments also demonstrate the ability of the KSOM or SSOM to classify emotions.

Název v anglickém jazyce

Self-Organizing Maps as Data Classifier in Medical Applications

Popis výsledku anglicky

Many researchers use mathematical-engineering methods in different domains of life, and medical research is no exception. One area for application of such methods is to assist people with different forms of disabilities. The methods described in the following text are oriented towards the analysis of disordered children's speech with the diagnosis of Specific Language Impairment (SLI), also named as Developmental Dysphasia (DD), and the analysis of the expressive speech. Both methods make use of KohonenSelf-Organizing Maps (KSOM) or Supervised Self-Organizing Maps (SSOM) for the analysis and the classification of features from utterances of healthy and ill children, or adult speakers for emotions analysis. The possibility of cluster visualisation is used for monitoring of disorder trends and therapy success. These experiments also demonstrate the ability of the KSOM or SSOM to classify emotions.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GA102%2F09%2F0989" target="_blank" >GA102/09/0989: Nové perspektivní metody vysoce kvalitní syntézy mluvené češtiny</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2011

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the International Conference on neural Computation Theory and Applications

ISBN

978-989-8425-84-3

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

422-429

Název nakladatele

SciTePress

Místo vydání

Madeira

Místo konání akce

Paris

Datum konání akce

24. 10. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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