Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Irene Vrbik"'
Autor:
Irene Vrbik, Samantha J Van Nest, Phiranuphon Meksiarun, Jason Loeppky, Alexandre Brolo, Julian J Lum, Andrew Jirasek
Publikováno v:
PLoS ONE, Vol 14, Iss 2, p e0212225 (2019)
Tumour heterogeneity plays a large role in the response of tumour tissues to radiation therapy. Inherent biological, physical, and even dose deposition heterogeneity all play a role in the resultant observed response. We here implement the use of Har
Externí odkaz:
https://doaj.org/article/9a01cc563a0a4957a9c13f78a122576b
Publikováno v:
CCECE
Open data published by various organizations is intended to make the data available to the public. All over the world, numerous organizations maintain a considerable number of open databases containing a lot of facts and numbers. However, most of the
Autor:
Alexandre G. Brolo, Irene Vrbik, Samantha J. Van Nest, Phiranuphon Meksiarun, Jason L. Loeppky, Julian J. Lum, Andrew Jirasek
Publikováno v:
PLoS ONE, Vol 14, Iss 2, p e0212225 (2019)
PLoS ONE
PLoS ONE
Tumour heterogeneity plays a large role in the response of tumour tissues to radiation therapy. Inherent biological, physical, and even dose deposition heterogeneity all play a role in the resultant observed response. We here implement the use of Har
Autor:
Paul D. McNicholas, Irene Vrbik
Publikováno v:
Statistics & Probability Letters. 82:1169-1174
The em algorithm can be used to compute maximum likelihood estimates of model parameters for skew- t mixture models. We show that the intractable expectations needed in the e -step can be written out analytically. These closed form expressions bypass
Publikováno v:
BMC Bioinformatics
Background In the context of infectious disease, sequence clustering can be used to provide important insights into the dynamics of transmission. Cluster analysis is usually performed using a phylogenetic approach whereby clusters are assigned on the
Autor:
Irene Vrbik, Paul D. McNicholas
Traditionally, there are three species of classification: unsupervised, supervised, and semi-supervised. Supervised and semi-supervised classification differ by whether or not weight is given to unlabelled observations in the classification procedure
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da481c9eace4ce17a75c12c44f5e6894
Publikováno v:
Bayesian Anal. 7, no. 3 (2012), 615-638
Individual-level models (ILMs), as defined by Deardon et al. (2010), are a class of models originally designed to model the spread of infectious disease. However, they can also be considered as a tool for modelling the spatio-temporal dynamics of fir