Using the patient's questionnaire data to screen laryngeal disorders

Abstract This paper is concerned with soft computing techniques for screening laryngeal disorders based on patient's questionnaire data. By applying the genetic search, the most important questionnaire statements are determined and a support vector machine (SVM) classifier is designed for categ...

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Bibliographic Details
Published in:Computers in biology and medicine 2009-02, Vol.39 (2), p.148-155
Main Authors: Verikas, A, Gelzinis, A, Bacauskiene, M, Uloza, V, Kaseta, M
Format: Article
Language:English
Subjects:
Automation
Curvilinear component analysis
Genetic search
Humans
Internal Medicine
Kirurgi
Laryngeal Diseases - diagnosis
Larynx pathology
MEDICIN
MEDICINE
Other
Otorhinolaryngologi
Otorhinolaryngology
Query data
Support vector machine
Surgery
Surveys and Questionnaires
Variable selection
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Summary:Abstract This paper is concerned with soft computing techniques for screening laryngeal disorders based on patient's questionnaire data. By applying the genetic search, the most important questionnaire statements are determined and a support vector machine (SVM) classifier is designed for categorizing the questionnaire data into the healthy , nodular and diffuse classes. To explore the obtained automated decisions, the curvilinear component analysis (CCA) in the space of decisions as well as questionnaire statements is applied. When testing the developed tools on the set of data collected from 180 patients, the classification accuracy of 85.0% was obtained. Bearing in mind the subjective nature of the data, the obtained classification accuracy is rather encouraging. The CCA allows obtaining ordered two-dimensional maps of the data in various spaces and facilitates the exploration of automated decisions provided by the system and determination of relevant groups of patients for various comparisons.
ISSN:0010-4825
1879-0534
1879-0534
DOI:10.1016/j.compbiomed.2008.11.008