Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View

Bibliographic Details
Main Author: Coimbra, Ana
Publication Date: 2016
Other Authors: Vicente, Henrique, Abelha, António, Santos, M. Filipe, Machado, José, Neves, João, Neves, José
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10174/19643
https://doi.org/10.1007/978-3-319-39630-9_10
Summary: 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%.
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spelling Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning ViewPreterm InfantsLength of StayNeonatologyKnowledge Representation and ReasoningLogic ProgrammingCase-Based ReasoningThe 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%.Springer International Publishing2017-01-09T18:07:24Z2017-01-092016-01-01T00:00:00Zbook partinfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10174/19643http://hdl.handle.net/10174/19643https://doi.org/10.1007/978-3-319-39630-9_10engCoimbra, 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.Cham, Switzerland978-3-319-39629-32190-3018http://link.springer.com/chapter/10.1007/978-3-319-39630-9_101ª14cecilia.coimbra@hotmail.comhvicente@uevora.ptabelha@di.uminho.ptmfs@dsi.uminho.ptjmac@di.uminho.ptjoaocpneves@gmail.comjneves@di.uminho.ptCoimbra, AnaVicente, HenriqueAbelha, AntónioSantos, M. FilipeMachado, JoséNeves, JoãoNeves, Joséinfo: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:RCAAP2024-01-03T19:07:21Zoai:dspace.uevora.pt:10174/19643Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T12:10:54.238064Repositórios 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 Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View
title Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View
spellingShingle Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View
Coimbra, Ana
Preterm Infants
Length of Stay
Neonatology
Knowledge Representation and Reasoning
Logic Programming
Case-Based Reasoning
title_short Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View
title_full Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View
title_fullStr Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View
title_full_unstemmed Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View
title_sort Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View
author Coimbra, Ana
author_facet Coimbra, Ana
Vicente, Henrique
Abelha, António
Santos, M. Filipe
Machado, José
Neves, João
Neves, José
author_role author
author2 Vicente, Henrique
Abelha, António
Santos, M. Filipe
Machado, José
Neves, João
Neves, José
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Coimbra, Ana
Vicente, Henrique
Abelha, António
Santos, M. Filipe
Machado, José
Neves, João
Neves, José
dc.subject.por.fl_str_mv Preterm Infants
Length of Stay
Neonatology
Knowledge Representation and Reasoning
Logic Programming
Case-Based Reasoning
topic Preterm Infants
Length of Stay
Neonatology
Knowledge Representation and Reasoning
Logic Programming
Case-Based Reasoning
description 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%.
publishDate 2016
dc.date.none.fl_str_mv 2016-01-01T00:00:00Z
2017-01-09T18:07:24Z
2017-01-09
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/10174/19643
http://hdl.handle.net/10174/19643
https://doi.org/10.1007/978-3-319-39630-9_10
url http://hdl.handle.net/10174/19643
https://doi.org/10.1007/978-3-319-39630-9_10
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 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.
Cham, Switzerland
978-3-319-39629-3
2190-3018
http://link.springer.com/chapter/10.1007/978-3-319-39630-9_10

14
cecilia.coimbra@hotmail.com
hvicente@uevora.pt
abelha@di.uminho.pt
mfs@dsi.uminho.pt
jmac@di.uminho.pt
joaocpneves@gmail.com
jneves@di.uminho.pt
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer International Publishing
publisher.none.fl_str_mv Springer International Publishing
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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