Evaluation of the Length of Hospital Stay through Artificial Neural Networks Based Systems
Main Author: | |
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Publication Date: | 2016 |
Other Authors: | , |
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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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 |
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IGI Global |
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