Aleksander B. Demko

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With the proliferation of high-dimensional biomedi-cal data, an acute need exists for a comprehensive, user-friendly software suite that allows investigators, in the health care disciplines, to classify their data through the detection of discriminating features. Scopira is a software initiative that attempts to achieve these goals in addition to providing(More)
We introduce a distance (similarity)-based mapping for the visualization of high-dimensional patterns and their relative relationships. The mapping preserves exactly the original distances between points with respect to any two reference patterns in a special two-dimensional coordinate system, the relative distance plane (RDP). As only a single calculation(More)
In MRI research labs, algorithms are typically implemented in MATLAB or IDL. If performance is an issue they are ported to C and integrated with interpreted systems, not fully utilizing object-oriented software development. This paper presents Scopira, an open source C++ framework suitable for MRI data analysis and visualization.
The automated prediction of qualitative attributes such as software complexity is a desirable software engineering goal. A potential technique is to use software metrics as quantitative predictors for these kinds of attributes. We describe a pattern classification method where a large collection of classifiers is presented with randomly selected subsets of(More)
Object-oriented visualization-based software systems for biomedical data analysis must deal with complex and voluminous datasets within a flexible yet intuitive graphical user interface. In a research environment, the development of such systems are difficult to manage due to rapidly changing requirements, incorporation of newly developed algorithms, and(More)
The analysis of feature variance is a common approach used for data interpretation. In the case of pattern classification, however, the transformation of correlated features into a new set of uncorrelated variables must be used with caution, as there is no necessary causal connection between discriminatory power and variance. To compensate for this(More)
With the rapid proliferation of complex high-dimensional biomedical data, an acute need exists for a comprehensive, knowledge-based, domain-specific, user-friendly software suite that allows investigators, in the health care disciplines, to classify their data through the detection of novel or discriminating features therein. The Classification Canvas is an(More)
Machine learning techniques are widely used in the analysis of biomedical datasets. Modern devices tend to produce voluminous, high-dimensional datasets for which medical practitioners require high-performance, user-friendly programs and researchers need effective algorithm development and testing platforms. Interactive development systems, such as MATIAB,(More)