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In the sections that follow, we present the results obtained in our effort to stratify the patients in high and low risk groups based on the reoccurrence probability.
Subsequently, the retained genes are employed as part of a series of classification schemes in order to discriminate the patients into high and low risk groups, in terms of reoccurrence probability.
The aim of the Baseline Data Analysis is to exploit the information from the baseline data of patients in order to compute the probability of a potential relapse, and consequently stratify the patients into high and low risk groups according to the reoccurrence probability.
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Based on the trained model, we are able to conjecture the values of all variables from future time-slices, including of course the probability of reoccurrence, by using the junction tree algorithm for inferencing from the DBN.
The relative error can be estimated by an expression depending on the percentage of the patients who were re-randomized, multipliers (how many times more likely it is to repeat an event) for the probability of reoccurrences, and the ratio of the total events reported and the initial number of patients entering the trial.
For some parameter estimates (e.g. probabilities of spontaneous remission, reoccurrence of depression and suicide rates) no measure of variability was available from the epidemiological evidence.
Can I prevent a reoccurrence?
But has anything changed to prevent the reoccurrence?
And what could the community do to forestall a reoccurrence?
Increased probability".
The consistency, the monotony, the certainty, all vagaries and passions are covered by this daily reoccurrence.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com