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Case-based decision support in time dependent medical domains

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Medical applications often require to capture the observed phenomenon dynamics, in order to properly support physicians' decision making. Case-based Reasoning (CBR), and more specifically case-based retrieval, is recently being recognized as a valuable decision support methodology in these domain. However, adopting CBR in this field is non trivial, since the need for describing the process dynamics impacts both on case representation and on the retrieval activity itself. In this work, we survey different methodologies introduced in the literature in order to implement medical CBR applications in time dependent domains, with a particular emphasis on time series representation and retrieval. Among the others, a novel approach, which relies on Temporal Abstractions, is analysed in depth.

Original languageEnglish
Title of host publicationArtificial Intelligence in Theory and Practice III - Third IFIP TC 12 International Conference on Artificial Intelligence, IFIP AI 2010, Held as Part of WCC 2010, Proceedings
EditorsMax Bramer
Pages238-242
Number of pages5
DOIs
Publication statusPublished - 2010
Event3rd IFIP TC 12 International Conference on Artificial Intelligence, IFIP AI 2010 - Brisbane, QLD, Australia
Duration: 20 Sept 201023 Sept 2010

Publication series

NameIFIP Advances in Information and Communication Technology
Volume331 AICT
ISSN (Print)1868-4238

Conference

Conference3rd IFIP TC 12 International Conference on Artificial Intelligence, IFIP AI 2010
Country/TerritoryAustralia
CityBrisbane, QLD
Period20/09/1023/09/10

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