Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/26347

Title: Evaluation of the Length of Hospital Stay through Artificial Neural Networks based Systems
Authors: Abelha, Vasco
Marins, Fernando
Vicente, Henrique
Editors: Information Resources Management Association
Keywords: Length of Hospital Stay
Healthcare
Logic Programming
Knowledge Representation and Reasoning
Artificial Neural Networks
Incomplete Information
Issue Date: 2020
Publisher: IGI Global
Citation: Abelha, V., Marins, F., & Vicente, H., Evaluation of the Length of Hospital Stay through Artificial Neural Networks based Systems. In Information Resources Management Association Ed., Hospital Management and Emergency Medicine: Breakthroughs in Research and Practice, pp. 391–403, IGI Global, Hershey, USA, 2020.
Abstract: The mentality of savings and eliminating any kind of outgoing costs is undermining our society and our way of living. Cutting funds from Education to Health is at best delaying the inevitable “Crash” that is foreshadowed. Regarding Health, a major concern, can be described as jeopardize the health of Patients – Reduce of the Length of Hospital. As we all know, Human Health is very sensitive and prune to drastic changes in short spaces of time. Factors like age, sex, their ambient context – house conditions, daily lives – should all be important when deciding how long a specific patient should remain safe in a hospital. In no way, ought this to be decided by the economic politics. Logic Programming was used for knowledge representation and reasoning, letting the modeling of the universe of discourse in terms of defective data, information and knowledge. Artificial Neural Networks and Genetic Algorithms were used in order to evaluate and predict how long should a patient remain in the hospital in order to minimize the collateral damage of our government approaches, not forgetting the use of Degree of Confidence to demonstrate how feasible the assessment is.
URI: https://www.igi-global.com/chapter/evaluation-of-the-length-of-hospital-stay-through-artificial-neural-networks-based-systems/246257
http://hdl.handle.net/10174/26347
ISBN: 9781799824510 (paper)
9781799824527 (electronic)
Type: bookPart
Appears in Collections:CQE - Publicações - Capítulos de Livros
QUI - Publicações - Capítulos de Livros

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