Extending temporal databases to deal with telic/atelic medical data

Paolo Terenziani, Richard T. Snodgrass, Alessio Bottrighi, Mauro Torchio, Gianpaolo Molino

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

7 Scopus citations

Abstract

In the area of Medical Informatics, there is an increasing realization that temporal information plays a crucial role, so that suitable database models and query languages are needed to store and support it. In this paper we show that current approaches developed within the database field have some limitations even from the point of view of the data model, so that an important class of temporal medical data cannot be properly represented. We propose a new three-sorted model and a query language that overcome such limitations.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Medicine - 10th Conference on Artificial Intelligence in Medicine, AIME 2005, Proceedings
PublisherSpringer-Verlag
Pages58-66
Number of pages9
ISBN (Print)3540278311, 9783540278313
DOIs
StatePublished - 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)0302-9743
ISSN (Electronic)1611-3349

Other

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

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Terenziani, P., Snodgrass, R. T., Bottrighi, A., Torchio, M., & Molino, G. (2005). Extending temporal databases to deal with telic/atelic medical data. In Artificial Intelligence in Medicine - 10th Conference on Artificial Intelligence in Medicine, AIME 2005, Proceedings (pp. 58-66). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3581 LNAI). Springer-Verlag. https://doi.org/10.1007/11527770_9