Measuring the implications of the D-basis in analysis of data in biomedical studies

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Abstract

We introduce the parameter of relevance of an attribute of a binary table to another attribute of the same table, computed with respect to an implicational basis of a closure system associated with the table. This enables a ranking of all attributes, by relevance parameter to the same fixed attribute, and, as a consequence, reveals the implications of the basis most relevant to this attribute. As an application of this new metric, we test the algorithm for D-basis extraction presented in Adaricheva and Nation [1] on biomedical data related to the survival groups of patients with particular types of cancer. Each test case requires a specialized approach in converting the real-valued data into binary data and careful analysis of the transformed data in a multi-disciplinary environment of cross-field collaboration.

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Adaricheva, K., Nation, J. B., Okimoto, G., Adarichev, V., Amanbekkyzy, A., Sarkar, S., … Alibek, K. (2015). Measuring the implications of the D-basis in analysis of data in biomedical studies. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 9113, pp. 39–57). Springer Verlag. https://doi.org/10.1007/978-3-319-19545-2_3

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