Discovery of Overlapping Clusters to detect Atherosclerosis Risk Factors

Abstract : This work presents a data mining effort to discover pure ‚or almost-pure clusters with respect to atherosclerosis risk factors, from a medical database used by the STULONG project. One originality of this work is to produce overlapping clusters with two recents algorithms: ECCLAT and PoBOC. Such clusters, described by social characteristics and physical and biochemical examinations on patients, allow to characterize patients affected by disease due to atherosclerosis, and may lead to relevant factors. We compare the two algorithms, and we observe if the results point out the role of some examinations.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-00084833
Contributor : Guillaume Cleuziou <>
Submitted on : Monday, July 10, 2006 - 5:07:48 PM
Last modification on : Tuesday, February 5, 2019 - 12:12:41 PM

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  • HAL Id : hal-00084833, version 1

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Nicolas Durand, Guillaume Cleuziou, Arnaud Soulet. Discovery of Overlapping Clusters to detect Atherosclerosis Risk Factors. -, 2004, -, France. ⟨hal-00084833⟩

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