Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/19719

Title: A Case-Based Approach to Nosocomial Infection Detection
Authors: Faria, Ricardo
Vicente, Henrique
Abelha, António
Santos, M. Filipe
Machado, José
Neves, José
Editors: Rutkowski, Leszek
Korytkowski, Marcin
Scherer, Rafal
Tadeusiewicz, Ryszard
Zadeh, Lotfi A.
Zurada, Jacek M.
Keywords: Nosocomial Infection
Healthcare
Knowledge Representation and Reasoning
Logic Programming
Case-Based Reasoning
Similarity Analysis
Issue Date: 2016
Publisher: Springer International Publishing
Citation: Faria, R., Vicente, H., Abelha, A., Santos, M. F., Machado, J. & Neves, J. A Case-Based Approach to Nosocomial Infection Detection. In L. Rutkowski, M. Korytkowski, R. Scherer, R. Tadeusiewicz, L. A. Zadeh & J. M. Zurada, Eds., Artificial Intelligence and Soft Computing, Lecture Notes in Artificial Intelligence, Vol. 9693, pp. 159–168, Springer International Publishing, Cham, Switzerland, 2016.
Abstract: The nosocomial infections are a growing concern because they affect a large number of people and they increase the admission time in healthcare facilities. Additionally, its diagnosis is very tricky, requiring multiple medical exams. So, this work is focused on the development of a clinical decision support system to prevent these events from happening. The proposed solution is unique once it caters for the explicit treatment of incomplete, unknown, or even contradictory information under a logic programming basis, that to our knowledge is something that happens for the first time.
URI: http://link.springer.com/chapter/10.1007/978-3-319-39384-1_14
http://hdl.handle.net/10174/19719
ISBN: 978-3-319-39383-4
ISSN: 0302-9743
Type: bookPart
Appears in Collections:QUI - Publicações - Capítulos de Livros

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