Mark A. Kon
Boston University
103 Papers
455 Citations
Mark A. Kon is an academic researcher from Boston University. The author has contributed to research in topics: Feature vector & Computer science. The author has an hindex of 19, co-authored 100 publications. Previous affiliations of Mark A. Kon include University of Warsaw & Massachusetts Institute of Technology.
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Papers
A new phylogenetic diversity measure generalizing the shannon index and its application to phyllostomid bats.
TL;DR: A new diversity index, the phylogenetic entropy, is introduced, which generalizes in a natural way the Shannon index to incorporate species relatedness and contrasts the behavior of multiple indices on a community of phyllostomid bats in the Selva Lacandona.
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Pointwise convergence of wavelet expansions
TL;DR: In this paper, it was shown that wavelet-type expansions (of functions in one or more dimensions) converge pointwise almost everywhere, and identify the Lebesgue set of a function as a set of full measure on which they converge.
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Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction
TL;DR: The k-TSP ranking algorithm can be used as a computationally efficient, multivariate filter method for feature selection in machine learning and appears to be a better feature selector than Fisher and RFE in some of the cancer datasets.
Biomedical Informatics for Computer-Aided Decision Support Systems: A Survey
TL;DR: A brief review of biomedical informatics systems in the form of computer-aided decision support, their application protocols and methodologies, and the future challenges and directions they suggest are provided.
Classification of malignant and benign tumors of the lung by infrared spectral histopathology (SHP)
Ali Akalin,Xinying Mu,Mark A. Kon,Aysegul Ergin,Stan Remiszewski,Clay M. Thompson,Dan J. Raz,Max Diem +7 more
TL;DR: A detailed comparison between classical and spectral histopathology is presented, suggesting that spectral Histopathology can achieve levels of diagnostic accuracy that is comparable to that of multipanel immunohistochemistry.
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