Prediction of chronic damage in systemic lupus erythematosus by using machine-learning models

Detalhes bibliográficos
Autor(a) principal: Ceccarelli, Fulvia
Data de Publicação: 2017
Outros Autores: Sciandrone, Marco, Perricone, Carlo, Galvan, Giulio, Morelli, Francesco, Vicente, Luís Nunes, Leccese, Ilaria, Massaro, Laura, Cipriano, Enrica, Spinelli, Francesca Romana, Alessandri, Cristiano, Valesini, Guido, Conti, Fabrizio
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/45495
https://doi.org/10.1371/journal.pone.0174200
Resumo: The increased survival in Systemic Lupus Erythematosus (SLE) patients implies the development of chronic damage, occurring in up to 50% of cases. Its prevention is a major goal in the SLE management. We aimed at predicting chronic damage in a large monocentric SLE cohort by using neural networks.
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spelling Prediction of chronic damage in systemic lupus erythematosus by using machine-learning modelsAdultDisease ProgressionFemaleHumansLongitudinal StudiesLupus Erythematosus, SystemicMachine LearningMaleSensitivity and SpecificitySeverity of Illness IndexThe increased survival in Systemic Lupus Erythematosus (SLE) patients implies the development of chronic damage, occurring in up to 50% of cases. Its prevention is a major goal in the SLE management. We aimed at predicting chronic damage in a large monocentric SLE cohort by using neural networks.Masataka Kuwana, Keio University, Japan2017info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/45495http://hdl.handle.net/10316/45495https://doi.org/10.1371/journal.pone.0174200enghttps://doi.org/10.1371/ journal.pone.0174200Ceccarelli, FulviaSciandrone, MarcoPerricone, CarloGalvan, GiulioMorelli, FrancescoVicente, Luís NunesLeccese, IlariaMassaro, LauraCipriano, EnricaSpinelli, Francesca RomanaAlessandri, CristianoValesini, GuidoConti, Fabrizioinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2020-05-25T12:11:45Zoai:estudogeral.uc.pt:10316/45495Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:53:25.253876Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Prediction of chronic damage in systemic lupus erythematosus by using machine-learning models
title Prediction of chronic damage in systemic lupus erythematosus by using machine-learning models
spellingShingle Prediction of chronic damage in systemic lupus erythematosus by using machine-learning models
Ceccarelli, Fulvia
Adult
Disease Progression
Female
Humans
Longitudinal Studies
Lupus Erythematosus, Systemic
Machine Learning
Male
Sensitivity and Specificity
Severity of Illness Index
title_short Prediction of chronic damage in systemic lupus erythematosus by using machine-learning models
title_full Prediction of chronic damage in systemic lupus erythematosus by using machine-learning models
title_fullStr Prediction of chronic damage in systemic lupus erythematosus by using machine-learning models
title_full_unstemmed Prediction of chronic damage in systemic lupus erythematosus by using machine-learning models
title_sort Prediction of chronic damage in systemic lupus erythematosus by using machine-learning models
author Ceccarelli, Fulvia
author_facet Ceccarelli, Fulvia
Sciandrone, Marco
Perricone, Carlo
Galvan, Giulio
Morelli, Francesco
Vicente, Luís Nunes
Leccese, Ilaria
Massaro, Laura
Cipriano, Enrica
Spinelli, Francesca Romana
Alessandri, Cristiano
Valesini, Guido
Conti, Fabrizio
author_role author
author2 Sciandrone, Marco
Perricone, Carlo
Galvan, Giulio
Morelli, Francesco
Vicente, Luís Nunes
Leccese, Ilaria
Massaro, Laura
Cipriano, Enrica
Spinelli, Francesca Romana
Alessandri, Cristiano
Valesini, Guido
Conti, Fabrizio
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Ceccarelli, Fulvia
Sciandrone, Marco
Perricone, Carlo
Galvan, Giulio
Morelli, Francesco
Vicente, Luís Nunes
Leccese, Ilaria
Massaro, Laura
Cipriano, Enrica
Spinelli, Francesca Romana
Alessandri, Cristiano
Valesini, Guido
Conti, Fabrizio
dc.subject.por.fl_str_mv Adult
Disease Progression
Female
Humans
Longitudinal Studies
Lupus Erythematosus, Systemic
Machine Learning
Male
Sensitivity and Specificity
Severity of Illness Index
topic Adult
Disease Progression
Female
Humans
Longitudinal Studies
Lupus Erythematosus, Systemic
Machine Learning
Male
Sensitivity and Specificity
Severity of Illness Index
description The increased survival in Systemic Lupus Erythematosus (SLE) patients implies the development of chronic damage, occurring in up to 50% of cases. Its prevention is a major goal in the SLE management. We aimed at predicting chronic damage in a large monocentric SLE cohort by using neural networks.
publishDate 2017
dc.date.none.fl_str_mv 2017
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/45495
http://hdl.handle.net/10316/45495
https://doi.org/10.1371/journal.pone.0174200
url http://hdl.handle.net/10316/45495
https://doi.org/10.1371/journal.pone.0174200
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://doi.org/10.1371/ journal.pone.0174200
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Masataka Kuwana, Keio University, Japan
publisher.none.fl_str_mv Masataka Kuwana, Keio University, Japan
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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