Using the patient's questionnaire data to screen laryngeal disorders

Authors:
A. Verikas;A. Gelzinis;M. Bacauskiene;V. Uloza;M. Kaseta
Affiliations:
Department of Applied Electronics, Kaunas University of Technology, Studentu 50, LT-51368 Kaunas, Lithuania and Intelligent Systems Laboratory, Halmstad University, Box 823, S 301 18 Halmstad, Swe ...;Department of Applied Electronics, Kaunas University of Technology, Studentu 50, LT-51368 Kaunas, Lithuania;Department of Applied Electronics, Kaunas University of Technology, Studentu 50, LT-51368 Kaunas, Lithuania;Department of Otolaryngology, Kaunas University of Medicine, LT-50009 Kaunas, Lithuania;Department of Otolaryngology, Kaunas University of Medicine, LT-50009 Kaunas, Lithuania
Venue:
Computers in Biology and Medicine
Year:
2009

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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.