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Mathematical analysis allows us to see the whole spectrum of possible outcomes, and provides a means to logically suggest ways to optimize treatment.
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In particular, our mathematical and statistical analysis allows for an examination of the several settings of electrical stimulation.
Our mathematical analysis theoretically allows a better accuracy since it is based on much more discrete measurements than in the system of Urano using only an unique half lysis point.
Texture analysis allows the detection of mathematical patterns in the gray-level distribution of the pixels.
The posterior pdfs for p0, n, μ m and μ p provide only slight modifications of the prior pdfs suggesting that the a priori mathematical analysis has allowed us to select these priors very effectively.
Cluster analysis allows the grouping of expression profiles with respect to their relative similarity or, in mathematical terms, a "distance".
We hope and anticipate that in the near future the accuracy and sensitivity of experiments will improve substantially, alongside a further sharpening of the mathematical and computational tools for their analysis, allowing for meaningful comparisons of interactomes.
An advantage of using these techniques is the ability to combine mathematical axes obtained in these analyses in a single cluster analysis, allowing analyzing of numerical and categorical variables simultaneously [ 43].
Mathematical manipulation of the information obtained in this analysis allowed a risk score to be allotted to each patient.
It also allows us to simplify the mathematical analysis to provide a theoretical bound on the resulting recovery error.
A method and equations for formulating a composite sustainability index as a function of relevant parameters, which thus allows mathematical analysis in general and sensitivity analysis and optimization in particular, are described.
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