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Recent advances of robotic/mechanical devices enable us to measure a subjectpsilas performance in an objective and precise manner. The main issue of using such devices is how to represent huge experimental data compactly in order to analyze and compare them with clinical data efficiently. In this paper, we choose a subset of features from real-time experimental data and build a classifier model to...
Gene expression data that is being used to gather information from tissue samples is expected to significantly improve the development of efficient tumor diagnosis and to provide understanding and insight into tumor related cellular processes. In this paper, we propose a novel feature selection approach which integrates the feature score criterion with factor analysis to further improve the SVM-based...
In this paper, we introduce a novel feature selection method that combines ant colony optimization (ACO) with support vector machine (SVM) to identify candidate biomarkers from mass spectral serum profiles. In addition, we present an innovative rule extraction algorithm that uses ACO to select accurate if-then rules for the classification of mass spectra. We applied the proposed feature selection...
One of the most frequent reasons for instituting mechanical ventilation is to decrease patient's work of breathing. Many attempts have been made to increase the effectiveness of the evaluation of the respiratory pattern with the analysis of the respiratory signals. This work proposes a method for the study of the differences in respiratory pattern variability in patients on weaning trials. The proposed...
One of the most frequent reasons for instituting mechanical ventilation is to decrease patient's work of breathing. Many attempts have been made to increase the effectiveness of the evaluation of the respiratory pattern with the analysis of the respiratory signals. This work proposes a method for the study of the differences in respiratory pattern variability in patients on weaning trials. The proposed...
This paper studies an intelligent system, including a support vector regression (SVR) and a similar analysis, for the classification of the ovarian cancer with microarray data. That is, steps in the classification include a feature selection step and a distance measure step. Firstly, the SVR is used to do the feature selection. That is, the SVR is applied to obtain the important genes of ovarian cancer...
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