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Exploiting image, voice, and patient's questionnaire for screening laryngeal disorders
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).ORCID iD: 0000-0003-2185-8973
Kaunas University of Medicine, Kaunas, Lithuania.
Kaunas University of Technology, Kaunas, Lithuania. (Department of Electrical & Control Equipment)
Kaunas University of Technology, Kaunas, Lithuania. (Department of Electrical & Control Equipment)
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2009 (English)In: Proceedings of the 3rdĀ Advanced Voice Function Assessement International Workshop (AVFA 2009), Madrid, 2009, p. 85-88Conference paper, Published paper (Refereed)
Abstract [en]

This paper is concerned with soft computing techniques for categorizing laryngeal disorders based on information extracted from an image of patient's vocal folds, a voice signal, and questionnaire data. Multiple feature sets are used to characterize images and voice signals. A committee of support vector machines (SVM) is designed for categorizing the data represented by the multiple feature sets into the healthy, nodular and diffuse classes. The feature selection and classifier design is combined into the same learning process based on genetic search. When testing the developed tools on the set of data collected from 240 patients, the classification accuracy of over 98.0% was obtained. Combination of the three modalities allowed to substantially improve the classification accuracy if compared to the highest accuracy obtained from a single modality.

Place, publisher, year, edition, pages
Madrid, 2009. p. 85-88
Keywords [en]
Larynx pathology, Classification, Variable selection, Genetic search, Support vector machine, Classification committee
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:hh:diva-111OAI: oai:DiVA.org:hh-111DiVA, id: diva2:236200
Conference
3rd Advanced Voice Function Assessement International Workshop (AVFA 2009), May 18-20, 2009, Madrid, Spain
Available from: 2009-09-21 Created: 2009-09-21 Last updated: 2018-01-13Bibliographically approved

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Verikas, Antanas

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf