Identification of thyroid gland activity in radioiodine therapy
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00472057" target="_blank" >RIV/67985556:_____/17:00472057 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.imu.2017.02.004" target="_blank" >http://dx.doi.org/10.1016/j.imu.2017.02.004</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.imu.2017.02.004" target="_blank" >10.1016/j.imu.2017.02.004</a>
Alternative languages
Result language
angličtina
Original language name
Identification of thyroid gland activity in radioiodine therapy
Original language description
The Bayesian identification of a linear regression model (called the biphasic model) for time dependence of thyroid gland activity in 131I radioiodine therapy is presented. Prior knowledge is elicited via hard parameter constraints and via the merging of external information from an archive of patient records. This prior regularization is shown to be crucial in the reported context, where data typically comprise only two or three high-noise measurements. The posterior distribution is simulated via a Langevin diffusion algorithm, whose optimization for the thyroid activity application is explained. Excellent patient-specific predictions of thyroid activity are reported. The posterior inference of the patient-specific total radiation dose is computed, allowing the uncertainty of the dose to be quantified in a consistent form. The relevance of this work in clinical practice is explained.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Informatics in Medicine Unlocked
ISSN
2352-9148
e-ISSN
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Volume of the periodical
7
Issue of the periodical within the volume
1
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
11
Pages from-to
23-33
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85016324996