| 1. |
- Bacauskiene, Marija, et al.
(författare)
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Random forests based monitoring of human larynx using questionnaire data
- 2012
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Ingår i: Expert systems with applications. - Amsterdam : Elsevier. - 0957-4174 .- 1873-6793. ; 39:5, s. 5506-5512
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Tidskriftsartikel (refereegranskat)abstract
- This paper is concerned with soft computing techniques-based noninvasive monitoring of human larynx using subject’s questionnaire data. By applying random forests (RF), questionnaire data are categorized into a healthy class and several classes of disorders including: cancerous, noncancerous, diffuse, nodular, paralysis, and an overall pathological class. The most important questionnaire statements are determined using RF variable importance evaluations. To explore data represented by variables used by RF, the t-distributed stochastic neighbor embedding (t-SNE) and the multidimensional scaling (MDS) are applied to the RF data proximity matrix. When testing the developed tools on a set of data collected from 109 subjects, the 100% classification accuracy was obtained on unseen data in binary classification into the healthy and pathological classes. The accuracy of 80.7% was achieved when classifying the data into the healthy, cancerous, noncancerous classes. The t-SNE and MDS mapping techniques applied allow obtaining two-dimensional maps of data and facilitate data exploration aimed at identifying subjects belonging to a “risk group”. It is expected that the developed tools will be of great help in preventive health care in laryngology.
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| 2. |
- Brorsson, Sofia, 1973-, et al.
(författare)
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Differences in the muscle activities in the forearm muscles in healthy men and women
- 2012
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Ingår i: Proceedings of the XIXth Congress of the International Society of Electrophysiology & Kinesiology. - Brisbane, Australia. - 9780646582283 ; , s. 437-437
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Konferensbidrag (refereegranskat)abstract
- Balance between flexor and extensor muscle activity is essential for optimal function. This has been demonstrated previously for the lower extremity, trunk and shoulder function, but information on the relationship in hand function is lacking. AIM: Was to evaluate whether there are qualitative differences in finger extension force(fef), grip force, force duration, force balance and the muscle activities in the forearm flexor and extensor muscles in healthy men and women in different ages.
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| 3. |
- Gelzinis, Adas, et al.
(författare)
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Boosting performance of the edge-based active contour model applied to phytoplankton images
- 2012
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Ingår i: Proceedings of the 13th IEEE International Symposium on Computational Intelligence and Informatics. - Piscataway, NJ : IEEE Press. - 9781467352062 - 9781467352055 - 9781467352109 ; , s. 273-277
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Konferensbidrag (refereegranskat)abstract
- Automated contour detection for objects representing the Prorocentrum minimum (P. minimum) species in phytoplankton images is the core goal of this study. The speciesis known to cause harmful blooms in many estuarine and coastal environments. Active contour model (ACM)-based image segmentation is the approach adopted here as a potential solution. Currently, the main research in ACM area is highly focused ondevelopment of various energy functions having some physical intuition. This work, by contrast, advocates the idea of rich and diverse image preprocessing before segmentation. Advantage of the proposed preprocessing is demonstrated experimentally by comparing it to the six well known active contour techniques applied to the cell segmentation in microscopy imagery task. © 2012 IEEE.
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| 4. |
- Gelzinis, Adas, et al.
(författare)
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Categorizing cells in phytoplankton images
- 2011
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Ingår i: Recent Advances in Signal Processing, Computational Geometry and Systems Theory. - Athens : World Scientific and Engineering Academy and Society. - 9781618040275 - 1618040278 ; , s. 82-87
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Konferensbidrag (refereegranskat)abstract
- This article is concerned with detection of invasive species---Prorocentrum minimum (P. minimum)---in phytoplankton images. The species is known to cause harmful blooms in many estuarine and coastal environments. A new technique, combining phase congruency-based detection of circular objects in images, stochastic optimization, image segmentation, and SVM and random forest-based classification of objects was developed to solve the task. The developed algorithms were tested using 114 images of 1280 x 960 pixels. There were 2088 P. minimum cells in the images in total. The algorithms were able to detect 93.25% of objects representing P. minimum cells and correctly classify 94.9% of all objects. The results are rather encouraging and will be used to develop an automated system for obtaining abundance estimates of the species.
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| 5. |
- Gelzinis, Adas, et al.
(författare)
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Detecting P. minimum cells in phytoplankton images
- 2011
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Ingår i: Electrical and Control Technologies : proceedings of the 6th international conference on Electrical and Control Technologies ECT 2011 / Kaunas University of Technology, IFAC Committee of National Lithuanian Organisation. - Kaunas, Lithuania : Kaunas University of Technology, Lithuania. ; , s. 61-66
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Konferensbidrag (refereegranskat)abstract
- This article is concerned with detection of objects in phytoplankton images, especially objects representing one invasive species-Prorocentrum minimum (P. minimum), - which is known to cause harmful blooms in many estuarine and coastal environments. A new technique, combining phase congruency-based detection of circular objects, stochastic optimization, and image segmentation was developed for solving the task. The developed algorithms were tested using 114 images of 1280x960 pixels size recorded by a colour camera. There were 2088 objects representing P. minimum cells in the images in total. The algorithms were able to detect 93,25% of the objects. The results are rather encouraging and may be applied for future development of the algorithms aimed at automated classification of objects into classes representing different phytoplankton species.
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| 6. |
- Gelzinis, Adas, et al.
(författare)
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Exploring sustained phonation recorded with acoustic and contact microphones to screen for laryngeal disorders
- 2014
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Ingår i: 2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE). - Piscataway, NJ : IEEE Press. - 9781479945276 - 9781479945269 ; , s. 125-132
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Konferensbidrag (refereegranskat)abstract
- Exploration of various features and different structures of data dependent random forests in screening for laryngeal disorders through analysis of sustained phonation recorded by acoustic and contact microphones is the main objective of this study. To obtain a versatile characterization of voice samples, 14 different sets of features were extracted and used to build an accurate classifier to distinguish between normal and pathological cases. We proposed a new, data dependent random forest-based, way to combine information available from the different feature sets. An approach to exploring data and decisions made by a random forest was also presented. Experimental investigations using a mixed gender database of 273 subjects have shown that the Perceptual linear predictive cepstral coefficients (PLPCC) was the best feature set for both microphones. However, the LP-coefficients and LPCT-coefficients feature sets exhibited good performance in the acoustic microphone case only. Models designed using the acoustic microphone data significantly outperformed the ones built using data recorded by the contact microphone. The contact microphone did not bring any additional information useful for classification. The proposed data dependent random forest significantly outperformed traditional designs. © 2014 IEEE.
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| 7. |
- Gelzinis, Adas, et al.
(författare)
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Learning Accurate Active Contours
- 2013
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Ingår i: Engineering Applications of Neural Networks. - Berlin Heidelberg : Springer Berlin/Heidelberg. - 9783642410123 - 9783642410130 ; , s. 396-405
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Konferensbidrag (refereegranskat)abstract
- Focus of research in Active contour models (ACM) area is mainly on development of various energy functions based on physical intuition. In this work, instead of designing a new energy function, we generate a multitude of contour candidates using various values of ACM parameters, assess their quality, and select the most suitable one for an object at hand. A random forest is trained to make contour quality assessments. We demonstrate experimentally superiority of the developed technique over three known algorithms in the P. minimum cells detection task solved via segmentation of phytoplankton images. © Springer-Verlag Berlin Heidelberg 2013.
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| 8. |
- Kalsyte, Zivile, et al.
(författare)
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A novel approach to designing an adaptive committee applied to predicting company’s future performance
- 2013
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Ingår i: Expert systems with applications. - Oxford : Pergamon Press. - 0957-4174 .- 1873-6793. ; 40:6, s. 2051-2057
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Tidskriftsartikel (refereegranskat)abstract
- This article presents an approach to designing an adaptive, data dependent, committee of models applied to prediction of several financial attributes for assessing company's future performance. Current liabilities/Current assets, Total liabilities/Total assets, Net income/Total assets, and Operating Income/Total liabilities are the attributes used in this paper. A self-organizing map (SOM) used for data mapping and analysis enables building committees, which are specific (committee size and aggregation weights) for each SOM node. The number of basic models aggregated into a committee and the aggregation weights depend on accuracy of basic models and their ability to generalize in the vicinity of the SOM node. A random forest is used a basic model in this study. The developed technique was tested on data concerning companies from ten sectors of the healthcare industry of the United States and compared with results obtained from averaging and weighted averaging committees. The proposed adaptivity of a committee size and aggregation weights led to a statistically significant increase in prediction accuracy if compared to other types of committees. © 2012 Elsevier Ltd. All rights reserved.
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| 9. |
- Kalsyte, Zivile, et al.
(författare)
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A Novel Technique to Design an Adaptive Committee of Models Applied to Predicting Company’s Future Performance
- 2013
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Ingår i: International Conference on Computer Research and Development. - New York, NY : ASME Press. - 9780791860182 ; , s. 65-70
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Konferensbidrag (refereegranskat)abstract
- This article presents an approach to designing an adaptive, data dependent, committee of models applied to prediction of several financial attributes for assessing company’s future performance. A self-organizing map (SOM) used for data mapping and analysis enables building committees, which are specific (committee size and aggregation weights) for each SOM node. The number of basic models aggregated into a committee and the aggregation weights depend on accuracy of basic models and their ability to generalize in the vicinity of the SOM node. The proposed technique led to a statistically significant increase in prediction accuracy if compared to other types of committees.
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| 10. |
- Minelga, Jonas, et al.
(författare)
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Comparing Throat and Acoustic Microphones for Laryngeal Pathology Detection from Human Voice
- 2014
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Ingår i: Electrical and Control Technologies. - Kaunas : Kaunas University of Technology. ; , s. 50-53
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Konferensbidrag (refereegranskat)abstract
- The aim of this study was to compare acoustic and throat microphones in the voice pathology detection task. Recordings of sustained phonation /a/ were used in the study. Each recording was characterized by a rather large set of diverse features, 1051 features in total. Classification into two classes, namely normal and pathological, was performed using random forest committees. Models trained using data obtained from the throat microphone provided lower classification accuracy. This is probably due to a narrower frequency range of the throat microphone leading to loss of important information. © Kaunas University of Technology, 2014.
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