Towards noninvasive screening for malignant tumours in human larynx

Abstract This article is concerned with soft computing-based noninvasive screening for malignant disorders in human larynx. The suitability of two types of data for the analysis is explored. The questionnaire data and the digital voice recordings of the sustained phonation of the vowel sound /a/ are...

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Bibliographic Details
Published in:Medical engineering & physics 2010-01, Vol.32 (1), p.83-89
Main Authors: Verikas, A, Gelzinis, A, Bacauskiene, M, Uloza, V
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Biological and medical sciences
Curvilinear component analysis
Female
Genetic search
Humans
Information technology
Informationsteknik
Laryngeal Neoplasms - diagnosis
Laryngeal Neoplasms - pathology
Larynx carcinoma
Male
Medical Oncology - methods
Medical sciences
Models, Statistical
Other information technology
Otorhinolaryngology. Stomatology
Pattern Recognition, Automated - methods
Query data
Radiology
Sound Spectrography
Speech Acoustics
Speech Production Measurement
Support vector machine
Surveys and Questionnaires
TECHNOLOGY
TEKNIKVETENSKAP
Tumors
Upper respiratory tract, upper alimentary tract, paranasal sinuses, salivary glands: diseases, semeiology
Voice acoustic analysis
Voice Quality
Övrig informationsteknik
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Summary:Abstract This article is concerned with soft computing-based noninvasive screening for malignant disorders in human larynx. The suitability of two types of data for the analysis is explored. The questionnaire data and the digital voice recordings of the sustained phonation of the vowel sound /a/ are the data types considered in this study. The screening is considered as a task of data classification into the h ealthy, cancerous , and noncancerous classes. To explore data and decisions a nonlinear mapping technique exhibiting the property of local data ordering is applied. The classification accuracy of over 92% was obtained for unseen questionnaire data collected from 240 subjects. The experimental investigations have shown that, concerning the three classes, the questionnaire data carry much more discriminative information than the voice signal. Two-dimensional plots created using the mapping technique provide further insights into the data and decisions obtained from the classifiers.
ISSN:1350-4533
1873-4030
1873-4030
DOI:10.1016/j.medengphy.2009.10.011