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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10174/19710
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Title: | Length of Stay in Intensive Care Units - A Case Base Evaluation |
Authors: | Silva, Ana Vicente, Henrique Abelha, António Santos, M. Filipe Machado, José Neves, João Neves, José |
Editors: | Fujita, Hamido Papadopoulos, George A. |
Keywords: | Intensive Care Unit Length of Stay Knowledge Representation and Reasoning Logic Programming Case-Based Reasoning Quality of Care |
Issue Date: | 2016 |
Publisher: | IOS Press |
Citation: | Silva, A., Vicente, H., Abelha, A., Santos, M. F., Machado, J., Neves, J. & Neves, J., Length of Stay in Intensive Care Units – A Case Base Evaluation. In H. Fujita & G. A. Papadopoulos Eds., New Trends in Software Methodologies, Tools and Techniques, Frontiers in Artificial Intelligence and Applications, Vol. 286, pp. 191–202, IOS Press, Amsterdam, Netherlands, 2016. |
Abstract: | As a matter of fact, an Intensive Care Unit (ICU) stands for a hospital facility where patients require close observation and monitoring. Indeed, predicting Length-of-Stay (LoS) at ICUs is essential not only to provide them with improved Quality-of-Care, but also to help the hospital management to cope with hospital resources. Therefore, in this work one`s aim is to present an Artificial Intelligence based Decision Support System to assist on the prediction of LoS at ICUs, which will be centered on a formal framework based on a Logic Programming acquaintance for knowledge representation and reasoning, complemented with a Case Based approach to computing, and able to handle unknown, incomplete, or even contradictory data, information or knowledge. |
URI: | http://ebooks.iospress.nl/publication/44441 http://hdl.handle.net/10174/19710 |
ISBN: | 978-1-61499-673-6 |
ISSN: | 0922-6389 |
Type: | bookPart |
Appears in Collections: | QUI - Publicações - Capítulos de Livros
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