Authors:
Andreia Silva
and
Cláudia Antunes
Affiliation:
Instituto Superior Técnico and University of Lisbon, Portugal
Keyword(s):
Healthcare, Hepatitis Dataset, Pattern Mining, Association Rules, Multi-dimensionality.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Data Mining
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
Huge amounts of data are continuously being generated in the healthcare system. A correct and careful analysis of these data may bring huge benefits to all people and processes involved in the healthcare management. However, the characteristics of healthcare data do not make this job easy. These data are usually too complex, massive, with high dimensionality, and are irregularly distributed over time. In the last decade, data mining has begun to address this area, providing the technology and approaches to transform these complex data into useful information for decision support. Multi-relational data mining, in particular, has gained attention since it aims for the discovery of frequent relations that involve multiple dimensions. In this work we present a case study on the healthcare domain. Using the Hepatitis dataset, we show how that data can be modeled and explored in a multi-dimensional model, and we present and discuss the results of applying a multi-dimensional data mining al
gorithm to that model.
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