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In a traditional school, the philosophy seems to be "the same method fits all".
Hence, they enable the means to develop and implement "one method fits all" patient-specific approaches to diagnosis and care.
Thus, the main element that differentiates a model-based system is the use of a physiologically relevant, validated model to create a patient-specific picture of patient state and provide patient-specific ("one method fits all") advice.
Hence, the critical difference is that model-based methods implicitly enforce a protocol, but, in their patient-specificity, translate the "one size fits all" approach of a fixed protocol to a "one method fits all" patient-specific form of care.
Similar(56)
However, Schurink et al. [ 14] used logistic regression fitting single SNP effects, while our Bayes-C method fitted all SNP simultaneously.
Since a Bayesian method simultaneously fits all SNPs into the model, a value of 0.1 was chosen so that the genotypes account for 90%% of the genetic variation.
There isn't a 'one size fits all' method of checking and maintaining health and safety levels," he says.
As a several billion pound industry encompassing everything from restaurants and bars, to hotels, amusement parks, cinemas and transportation, there is no "one size fits all" method of finding success.
When it comes to dividing out housework, I don't think there is one "one size fits all" method.
Therefore, health care providers need to move from a 'one size fits all' method of providing information to a more patient specific approach that considers the unique needs of each patient.
We hypothesize it may not be possible to find a "one size fits all" normalization method.
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