Artificial neural networks to evaluate the boron concentration decreasing profile in Blood-BPA samples of BNCT patients

Autores
Garcia Reiriz, Alejandro Gabriel; Magallanes, Jorge Federico; Zupan, Jure; Líberman, Sara
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
For the prediction of decay concentration profiles of the p-boronophenylalanine (BPA) in blood during BNCT treatment, a method is suggested based on Kohonen neural networks. The results of a model trained with the concentration profiles from the literature are described. The prediction of the model was validated by the leave-one-out method. Its robustness shows that it is mostly independent on small variations. The ability to fit retrospective experimental data shows an uncertainty lower than the two compartment model used previously.
Fil: Garcia Reiriz, Alejandro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Magallanes, Jorge Federico. Comisión Nacional de Energía Atómica; Argentina
Fil: Zupan, Jure. National Institute of Chemistry; Eslovenia
Fil: Líberman, Sara. Comisión Nacional de Energía Atómica; Argentina
Materia
Kohonen neural networks
BNCT
Concentration profile prediction
p-Boronophenylalanie
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/108002
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Artificial neural networks to evaluate the boron concentration decreasing profile in Blood-BPA samples of BNCT patientsGarcia Reiriz, Alejandro GabrielMagallanes, Jorge FedericoZupan, JureLíberman, SaraKohonen neural networksBNCTConcentration profile predictionp-Boronophenylalaniehttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1For the prediction of decay concentration profiles of the p-boronophenylalanine (BPA) in blood during BNCT treatment, a method is suggested based on Kohonen neural networks. The results of a model trained with the concentration profiles from the literature are described. The prediction of the model was validated by the leave-one-out method. Its robustness shows that it is mostly independent on small variations. The ability to fit retrospective experimental data shows an uncertainty lower than the two compartment model used previously.Fil: Garcia Reiriz, Alejandro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; ArgentinaFil: Magallanes, Jorge Federico. Comisión Nacional de Energía Atómica; ArgentinaFil: Zupan, Jure. National Institute of Chemistry; EsloveniaFil: Líberman, Sara. Comisión Nacional de Energía Atómica; ArgentinaPergamon-Elsevier Science Ltd2011-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/108002Garcia Reiriz, Alejandro Gabriel; Magallanes, Jorge Federico; Zupan, Jure; Líberman, Sara; Artificial neural networks to evaluate the boron concentration decreasing profile in Blood-BPA samples of BNCT patients; Pergamon-Elsevier Science Ltd; Applied Radiation and Isotopes; 69; 12; 12-2011; 1793-17950969-8043CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0969804311002600info:eu-repo/semantics/altIdentifier/doi/10.1016/j.apradiso.2011.02.055info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:37:50Zoai:ri.conicet.gov.ar:11336/108002instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 15:37:50.7CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Artificial neural networks to evaluate the boron concentration decreasing profile in Blood-BPA samples of BNCT patients
title Artificial neural networks to evaluate the boron concentration decreasing profile in Blood-BPA samples of BNCT patients
spellingShingle Artificial neural networks to evaluate the boron concentration decreasing profile in Blood-BPA samples of BNCT patients
Garcia Reiriz, Alejandro Gabriel
Kohonen neural networks
BNCT
Concentration profile prediction
p-Boronophenylalanie
title_short Artificial neural networks to evaluate the boron concentration decreasing profile in Blood-BPA samples of BNCT patients
title_full Artificial neural networks to evaluate the boron concentration decreasing profile in Blood-BPA samples of BNCT patients
title_fullStr Artificial neural networks to evaluate the boron concentration decreasing profile in Blood-BPA samples of BNCT patients
title_full_unstemmed Artificial neural networks to evaluate the boron concentration decreasing profile in Blood-BPA samples of BNCT patients
title_sort Artificial neural networks to evaluate the boron concentration decreasing profile in Blood-BPA samples of BNCT patients
dc.creator.none.fl_str_mv Garcia Reiriz, Alejandro Gabriel
Magallanes, Jorge Federico
Zupan, Jure
Líberman, Sara
author Garcia Reiriz, Alejandro Gabriel
author_facet Garcia Reiriz, Alejandro Gabriel
Magallanes, Jorge Federico
Zupan, Jure
Líberman, Sara
author_role author
author2 Magallanes, Jorge Federico
Zupan, Jure
Líberman, Sara
author2_role author
author
author
dc.subject.none.fl_str_mv Kohonen neural networks
BNCT
Concentration profile prediction
p-Boronophenylalanie
topic Kohonen neural networks
BNCT
Concentration profile prediction
p-Boronophenylalanie
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv For the prediction of decay concentration profiles of the p-boronophenylalanine (BPA) in blood during BNCT treatment, a method is suggested based on Kohonen neural networks. The results of a model trained with the concentration profiles from the literature are described. The prediction of the model was validated by the leave-one-out method. Its robustness shows that it is mostly independent on small variations. The ability to fit retrospective experimental data shows an uncertainty lower than the two compartment model used previously.
Fil: Garcia Reiriz, Alejandro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Magallanes, Jorge Federico. Comisión Nacional de Energía Atómica; Argentina
Fil: Zupan, Jure. National Institute of Chemistry; Eslovenia
Fil: Líberman, Sara. Comisión Nacional de Energía Atómica; Argentina
description For the prediction of decay concentration profiles of the p-boronophenylalanine (BPA) in blood during BNCT treatment, a method is suggested based on Kohonen neural networks. The results of a model trained with the concentration profiles from the literature are described. The prediction of the model was validated by the leave-one-out method. Its robustness shows that it is mostly independent on small variations. The ability to fit retrospective experimental data shows an uncertainty lower than the two compartment model used previously.
publishDate 2011
dc.date.none.fl_str_mv 2011-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/108002
Garcia Reiriz, Alejandro Gabriel; Magallanes, Jorge Federico; Zupan, Jure; Líberman, Sara; Artificial neural networks to evaluate the boron concentration decreasing profile in Blood-BPA samples of BNCT patients; Pergamon-Elsevier Science Ltd; Applied Radiation and Isotopes; 69; 12; 12-2011; 1793-1795
0969-8043
CONICET Digital
CONICET
url http://hdl.handle.net/11336/108002
identifier_str_mv Garcia Reiriz, Alejandro Gabriel; Magallanes, Jorge Federico; Zupan, Jure; Líberman, Sara; Artificial neural networks to evaluate the boron concentration decreasing profile in Blood-BPA samples of BNCT patients; Pergamon-Elsevier Science Ltd; Applied Radiation and Isotopes; 69; 12; 12-2011; 1793-1795
0969-8043
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0969804311002600
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.apradiso.2011.02.055
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1846083498252697600
score 13.22299

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