Using temporal constraints to integrate signal analysis and domain knowledge in medical event detection

Feng Gao, Yaji Sripada, Jim Hunter, Francois Portet

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

7 Citations (Scopus)

Abstract

The events which occur in an Intensive Care Unit (ICU) are many and varied. Very often, events which are important to an understanding of what has happened to the patient are not recorded in the electronic patient record. This paper describes an approach to the automatic detection of such unrecorded 'target' events which brings together signal analysis to generate temporal patterns, and temporal constraint networks to integrate these patterns with other associated events which are manually or automatically recorded. This approach has been tested on real data recorded in a Neonatal ICU with positive results.
Original languageEnglish
Title of host publicationAIME-09
Subtitle of host publicationProceedings of the Twelfth European Conference on Artificial Intelligence in Medicine
EditorsCarlo Combi, Yuval Shahar, Ameen Abu-Hanna
PublisherSpringer-Verlag
Pages46-55
Number of pages10
Volume5651
ISBN (Electronic)978-3-642-02976-9
ISBN (Print)3-642-02975-2
DOIs
Publication statusPublished - 10 Jul 2009

Publication series

NameLecture Notes in Artificial Intelligence

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Gao, F., Sripada, Y., Hunter, J., & Portet, F. (2009). Using temporal constraints to integrate signal analysis and domain knowledge in medical event detection. In C. Combi, Y. Shahar, & A. Abu-Hanna (Eds.), AIME-09: Proceedings of the Twelfth European Conference on Artificial Intelligence in Medicine (Vol. 5651, pp. 46-55). (Lecture Notes in Artificial Intelligence). Springer-Verlag. https://doi.org/10.1007/978-3-642-02976-9_6