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Co-occurrence patterns in diagnostic data

Author
Piceno, M.; Rodríguez-Navas, L.; Balcazar, J. L.
Type of activity
Journal article
Journal
Computational intelligence
Date of publication
2020-04-12
First page
1
Last page
16
DOI
10.1111/coin.12317
Project funding
A unified theory of algorithmic relaxations
Management and Analysis of Complex DATA
Repository
http://hdl.handle.net/2117/185390 Open in new window
URL
https://onlinelibrary.wiley.com/doi/full/10.1111/coin.12317 Open in new window
Abstract
We demonstrate how graph decomposition techniques can be employed for the visualization of hierarchical co-occurrence patterns between medical data items. Our research is based on Gaifman graphs (a mathematical concept introduced in Logic), on specific variants of this concept, and on existing graph decomposition notions, specifically, graph modules and the clan decomposition of so-called 2-structures. The construction of the Gaifman graphs from a dataset is based on co-occurrence, or lack of it...
Citation
Piceno, M.; Rodríguez-Navas, L.; Balcázar, J. L. Co-occurrence patterns in diagnostic data. "Computational intelligence", 12 Abril 2020, p. 1-16.
Keywords
Clan decomposition, Exploratory data analysis, Gaifman graphs
Group of research
LARCA - Laboratory of Relational Algorithmics, Complexity and Learnability

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