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A new inverse regression model applied to radiation biodosimetry

Biological dosimetry based on chromosome aberration scoring in peripheral blood lymphocytes enables timely assessment of the ionizing radiation dose absorbed by an individual. Here, new Bayesian-type count data inverse regression methods are introduced for situations where responses are Poisson or t...

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Detalles Bibliográficos
Autores principales: Higueras, Manuel, Puig, Pedro, Ainsbury, Elizabeth A., Rothkamm, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4309124/
https://www.ncbi.nlm.nih.gov/pubmed/25663804
http://dx.doi.org/10.1098/rspa.2014.0588
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author Higueras, Manuel
Puig, Pedro
Ainsbury, Elizabeth A.
Rothkamm, Kai
author_facet Higueras, Manuel
Puig, Pedro
Ainsbury, Elizabeth A.
Rothkamm, Kai
author_sort Higueras, Manuel
collection PubMed
description Biological dosimetry based on chromosome aberration scoring in peripheral blood lymphocytes enables timely assessment of the ionizing radiation dose absorbed by an individual. Here, new Bayesian-type count data inverse regression methods are introduced for situations where responses are Poisson or two-parameter compound Poisson distributed. Our Poisson models are calculated in a closed form, by means of Hermite and negative binomial (NB) distributions. For compound Poisson responses, complete and simplified models are provided. The simplified models are also expressible in a closed form and involve the use of compound Hermite and compound NB distributions. Three examples of applications are given that demonstrate the usefulness of these methodologies in cytogenetic radiation biodosimetry and in radiotherapy. We provide R and SAS codes which reproduce these examples.
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spelling pubmed-43091242015-02-08 A new inverse regression model applied to radiation biodosimetry Higueras, Manuel Puig, Pedro Ainsbury, Elizabeth A. Rothkamm, Kai Proc Math Phys Eng Sci Research Articles Biological dosimetry based on chromosome aberration scoring in peripheral blood lymphocytes enables timely assessment of the ionizing radiation dose absorbed by an individual. Here, new Bayesian-type count data inverse regression methods are introduced for situations where responses are Poisson or two-parameter compound Poisson distributed. Our Poisson models are calculated in a closed form, by means of Hermite and negative binomial (NB) distributions. For compound Poisson responses, complete and simplified models are provided. The simplified models are also expressible in a closed form and involve the use of compound Hermite and compound NB distributions. Three examples of applications are given that demonstrate the usefulness of these methodologies in cytogenetic radiation biodosimetry and in radiotherapy. We provide R and SAS codes which reproduce these examples. The Royal Society Publishing 2015-02-08 /pmc/articles/PMC4309124/ /pubmed/25663804 http://dx.doi.org/10.1098/rspa.2014.0588 Text en http://creativecommons.org/licenses/by/4.0/ © 2015 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Research Articles
Higueras, Manuel
Puig, Pedro
Ainsbury, Elizabeth A.
Rothkamm, Kai
A new inverse regression model applied to radiation biodosimetry
title A new inverse regression model applied to radiation biodosimetry
title_full A new inverse regression model applied to radiation biodosimetry
title_fullStr A new inverse regression model applied to radiation biodosimetry
title_full_unstemmed A new inverse regression model applied to radiation biodosimetry
title_short A new inverse regression model applied to radiation biodosimetry
title_sort new inverse regression model applied to radiation biodosimetry
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4309124/
https://www.ncbi.nlm.nih.gov/pubmed/25663804
http://dx.doi.org/10.1098/rspa.2014.0588
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