Evaluation of the Length of Hospital Stay through Artificial Neural Networks Based Systems

Bibliographic Details
Main Author: Abelha, Vasco
Publication Date: 2016
Other Authors: Marins, Fernando, Vicente, Henrique
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10174/17402
https://doi.org/10.4018/978-1-4666-9882-6.ch008
Summary: 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.
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spelling Evaluation of the Length of Hospital Stay through Artificial Neural Networks Based SystemsLength of Hospital StayHealthcareLogic ProgrammingKnowledge Representation and ReasoningArtificial Neural NetworksIncomplete InformationThe 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.IGI Global2016-02-17T17:43:38Z2016-02-172016-01-01T00:00:00Zbook partinfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10174/17402http://hdl.handle.net/10174/17402https://doi.org/10.4018/978-1-4666-9882-6.ch008engAbelha, V., Marins, F., Vicente, H. & Neves, J., Evaluation of the Length of Hospital Stay through Artificial Neural Networks based Systems. In J. Machado & A. Abelha, Eds., Applying Business Intelligence to Clinical and Healthcare Organizations, Advances in Bioinformatics and Biomedical Engineering, pp. 153–168, IGI Global, Hershey, USA, 2016.Hershey, USA9781466698826http://www.igi-global.com/chapter/evaluation-of-the-length-of-hospital-stay-through-artificial-neural-networks-based-systems/146067168 - Evaluation of the Length of Hospital Stay through Artificial Neural Networks Based SystemsDQUIvascoabelha91@gmail.comf.abreu.marins@gmail.comhvicente@uevora.ptAbelha, VascoMarins, FernandoVicente, Henriqueinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-01-03T19:04:51Zoai:dspace.uevora.pt:10174/17402Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T12:09:22.595998Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Evaluation of the Length of Hospital Stay through Artificial Neural Networks Based Systems
title Evaluation of the Length of Hospital Stay through Artificial Neural Networks Based Systems
spellingShingle Evaluation of the Length of Hospital Stay through Artificial Neural Networks Based Systems
Abelha, Vasco
Length of Hospital Stay
Healthcare
Logic Programming
Knowledge Representation and Reasoning
Artificial Neural Networks
Incomplete Information
title_short Evaluation of the Length of Hospital Stay through Artificial Neural Networks Based Systems
title_full Evaluation of the Length of Hospital Stay through Artificial Neural Networks Based Systems
title_fullStr Evaluation of the Length of Hospital Stay through Artificial Neural Networks Based Systems
title_full_unstemmed Evaluation of the Length of Hospital Stay through Artificial Neural Networks Based Systems
title_sort Evaluation of the Length of Hospital Stay through Artificial Neural Networks Based Systems
author Abelha, Vasco
author_facet Abelha, Vasco
Marins, Fernando
Vicente, Henrique
author_role author
author2 Marins, Fernando
Vicente, Henrique
author2_role author
author
dc.contributor.author.fl_str_mv Abelha, Vasco
Marins, Fernando
Vicente, Henrique
dc.subject.por.fl_str_mv Length of Hospital Stay
Healthcare
Logic Programming
Knowledge Representation and Reasoning
Artificial Neural Networks
Incomplete Information
topic Length of Hospital Stay
Healthcare
Logic Programming
Knowledge Representation and Reasoning
Artificial Neural Networks
Incomplete Information
description 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.
publishDate 2016
dc.date.none.fl_str_mv 2016-02-17T17:43:38Z
2016-02-17
2016-01-01T00:00:00Z
dc.type.driver.fl_str_mv book part
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10174/17402
http://hdl.handle.net/10174/17402
https://doi.org/10.4018/978-1-4666-9882-6.ch008
url http://hdl.handle.net/10174/17402
https://doi.org/10.4018/978-1-4666-9882-6.ch008
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Abelha, V., Marins, F., Vicente, H. & Neves, J., Evaluation of the Length of Hospital Stay through Artificial Neural Networks based Systems. In J. Machado & A. Abelha, Eds., Applying Business Intelligence to Clinical and Healthcare Organizations, Advances in Bioinformatics and Biomedical Engineering, pp. 153–168, IGI Global, Hershey, USA, 2016.
Hershey, USA
9781466698826
http://www.igi-global.com/chapter/evaluation-of-the-length-of-hospital-stay-through-artificial-neural-networks-based-systems/146067
16
8 - Evaluation of the Length of Hospital Stay through Artificial Neural Networks Based Systems
DQUI
vascoabelha91@gmail.com
f.abreu.marins@gmail.com
hvicente@uevora.pt
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv IGI Global
publisher.none.fl_str_mv IGI Global
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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