Next Article in Journal
A Hardware-Efficient Vector Quantizer Based on Self-Organizing Map for High-Speed Image Compression
Previous Article in Journal
Feature Selection and Classification of Ulcerated Lesions Using Statistical Analysis for WCE Images
Article Menu
Issue 10 (October) cover image

Export Article

Open AccessArticle
Appl. Sci. 2017, 7(10), 1096;

A Transparent Decision Support Tool in Screening for Laryngeal Disorders Using Voice and Query Data

Department of Electric Power Systems, Kaunas University of Technology, Studentu 50, LT-51368 Kaunas, Lithuania
Centre for Applied Intelligent Systems Research, Halmstad University, Kristian IV:s väg 3, P.O. Box 823, S-30118 Halmstad, Sweden
Author to whom correspondence should be addressed.
Received: 4 September 2017 / Accepted: 20 October 2017 / Published: 24 October 2017
Full-Text   |   PDF [441 KB, uploaded 24 October 2017]   |  


The aim of this study is a transparent tool for analysis of voice (sustained phonation /a/) and query data capable of providing support in screening for laryngeal disorders. In this work, screening is concerned with identification of potentially pathological cases by classifying subject’s data into ’healthy’ and ’pathological’ classes as well as visual exploration of data and automatic decisions. A set of association rules and a decision tree, techniques lending themselves for exploration, were generated for pathology detection. Data pairwise similarities, estimated in a novel way, were mapped onto a 2D metric space for visual inspection and analysis. Accurate identification of pathological cases was observed on unseen subjects using the most discriminative query parameter and six audio parameters routinely used by otolaryngologists in a clinical practice: equal error rate (EER) of 11.1% was achieved using association rules and 10.2% using the decision tree. The EER was further reduced to 9.5% by combining results from these two classifiers. The developed solution can be a useful tool for Otolaryngology departments in diagnostics, education and exploratory tasks. View Full-Text
Keywords: decision tree; t-SNE visualization; association rules; pathological voice decision tree; t-SNE visualization; association rules; pathological voice

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Minelga, J.; Verikas, A.; Vaiciukynas, E.; Gelzinis, A.; Bacauskiene, M. A Transparent Decision Support Tool in Screening for Laryngeal Disorders Using Voice and Query Data. Appl. Sci. 2017, 7, 1096.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top