The statistical models selected are Relevance Vector Machine (RVM), an implementation of Sparse Bayesian Learning, and the Automated Statistical Downscaling tool (ASD), an implementation of Multiple Linear Regression.
In order to investigate whether observations made in the preclinical glioblastoma model are of relevance for human GBM, we analyzed patient‐derived tumor samples before and after therapy.
We believe that the cost-effectiveness estimates provided by this model are of relevance to patient care, given the long-term control of arrhythmia that may be required by AF/AFL patients.
Several of the components described as key elements in the "Chronic Care Model" are of relevance to patients with ESRD: Individual follow-up by informed health care personnel; decision support; and a proactive care plan on how to meet complications.
Analysis of data derived from such experiments should be interpreted in the context of stochastic systems and we feel that it is of practical value to the broader community of researchers to present concrete examples of these issues using a hypothetical model that is relevance to the fundamental transcription-translation-metabolism scheme.
These data lend support to the idea that nutrient restriction genuinely extends lifespan in flies, and that any mechanistic discoveries made with this model are of potential relevance to the determinants of lifespan in other organisms.
Moreover, results generated from our model are of great relevance for future clinical investigations.
Since the endotoxemia model utilizes LPS, rather than intact bacteria, there is an ongoing concern that data derived from this model are of limited relevance to our understanding of sepsis-induced inflammatory mechanisms, although recent analyses of the leukocyte transcriptome seemed to argue otherwise [ 15].
After estimation of the TFA of DosR based on a number of known target genes using the GP model, we predict novel DosR-regulated genes: the parameters of the model are interpreted as relevance parameters indicating an existing functional relationship between TFA and gene expression.
The parameters of the model are based on relevance scores of suggested MeSH terms: where s(c, Q) is the classification score assigned to MeSH concept c for the query and Q C is the set of terms suggested by the system.
