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|Title: ||Length of Stay in Intensive Care Units - A Case Base Evaluation|
|Authors: ||Silva, Ana|
Santos, M. Filipe
|Editors: ||Fujita, Hamido|
Papadopoulos, George A.
|Keywords: ||Intensive Care Unit|
Length of Stay
Knowledge Representation and 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.|
|Appears in Collections:||QUI - Publicações - Capítulos de Livros|
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