Knowledge discovery steps

Machine learning is defined as the use of algorithms to generate a model from data, which is one step in the knowledge discovery process, applied in the context... 

The knowledge discovery basis of PM modeling permits the generation of hypotheses from the relationship discovered during data structure analysis. These relationships can be tested in the nonlinear mixed effects modeling step. It can... 

Step 2. A data set and/or a valid model summarizing the discovered knowledge from a prior PK/PD knowledge discovery process. 

Recovery. In the 2000 Washington Conference final report it is clearly stated that knowledge of recovery is not essential to assay validation, but it does provide useful information about the real amount of analyte that is being analyzed. Assessment of recovery at every step of sample preparation and analysis in which losses may occur provides a powerful diagnostic tool to improve the method if needed. If a good internal standard has been chosen, the losses will have no impact on quantitation because they will be similar for analyte and internal standard and will thus annul each other. On the other hand, recovery is very important to verify if the internal standard really mimics and matches the analyte. The discovery of significant and inconsistent differences in recovery between analyte and internal standard at different steps of sample cleanup and analysis could indicate possible failure of the method during the validation. 

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