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Title: Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View
Authors: Coimbra, Ana
Vicente, Henrique
Abelha, António
Santos, M. Filipe
Machado, José
Neves, João
Neves, José
Editors: Czarnowski, Ireneusz
Caballero, Alfonso M.
Howlett, Robert J.
Jain, Lakhmi C.
Keywords: Preterm Infants
Length of Stay
Knowledge Representation and Reasoning
Logic Programming
Case-Based Reasoning
Issue Date: 2016
Publisher: Springer International Publishing
Citation: Coimbra, A., Vicente, H., Abelha, A., Santos, M. F., Machado, J., Neves, J. & Neves, J. Prediction of Length of Hospital Stay in Preterm Infants – A Case-Based Reasoning View. In I. Czarnowski, A. M. Caballero, R. J. Howlett & L. C. Jain, Eds., Intelligent Decision Technologies 2016 – Vol. 1, Smart Innovation, Systems and Technologies, Vol. 56, pp. 115–128, Springer International Publishing, Cham, Switzerland, 2016.
Abstract: The length of stay of preterm infants in a neonatology service has become an issue of a growing concern, namely considering, on the one hand, the mothers and infants health conditions and, on the other hand, the scarce healthcare facilities own resources. Thus, a pro-active strategy for problem solving has to be put in place, either to improve the quality-of-service provided or to reduce the inherent financial costs. Therefore, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a case-based problem solving methodology to computing, that caters for the handling of incomplete, unknown, or even contradictory in-formation. The proposed model has been quite accurate in predicting the length of stay (overall accuracy of 84.9%) and by reducing the computational time with values around 21.3%.
ISBN: 978-3-319-39629-3
ISSN: 2190-3018
Type: bookPart
Appears in Collections:QUI - Publicações - Capítulos de Livros

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