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|Title: ||Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View|
|Authors: ||Coimbra, Ana|
Santos, M. Filipe
|Editors: ||Czarnowski, Ireneusz|
Caballero, Alfonso M.
Howlett, Robert J.
Jain, Lakhmi C.
|Keywords: ||Preterm Infants|
Length of Stay
Knowledge Representation and 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%.|
|Appears in Collections:||QUI - Publicações - Capítulos de Livros|
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