Learning rules with complex temporal patterns in biomedical domains

Lucia Sacchi, Riccardo Bellazzi, Cristiana Larizza, Riccardo Porreca, Paolo Magni

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a novel algorithm for extracting rules expressing complex patterns from temporal data. Typically, a temporal rule describes a temporal relationship between the antecedent and the consequent, which are often time-stamped events. In this paper we introduce a new method to learn rules with complex temporal patterns in both the antecedent and the consequent, which can be applied in a variety of biomedical domains. Within the proposed approach, the user defines a set of complex interesting patterns that will constitute the basis for the construction of the temporal rules. Such complex patterns are represented with a Temporal Abstraction formalism. An APRIORI-like algorithm then extracts precedence temporal relationships between the complex patterns. The paper presents the results obtained by the rule extraction algorithm in two different biomedical applications. The first domain is the analysis of time series coming from the monitoring of hemodialysis sessions, while the other deals with the biological problem of inferring regulatory networks from gene expression data.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages23-32
Number of pages10
Volume3581 LNAI
Publication statusPublished - 2005
Event10th Conference on Artificial Intelligence in Medicine, AIME 2005 - Aberdeen, United Kingdom
Duration: Jul 23 2005Jul 27 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3581 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other10th Conference on Artificial Intelligence in Medicine, AIME 2005
CountryUnited Kingdom
CityAberdeen
Period7/23/057/27/05

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

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