This cohort has proved to be a remarkably informative resource, providing a temporal profile of leukemia and cancer associated with the blast and a robust data set for making quantitative estimates of risk.
However, making quantitative predictions with such models often requires parameter estimation from data, raising questions of parameter identifiability and estimability.
Nonetheless, lack of accurate data combined with inconsistent routines for registering data made quantitative comparisons between the three cases difficult.
The reliability of the Ollerenshaw index is further substantiated by the agreement between the map of current risk levels and the latest fasciolosis prevalence data [33], however the lack of long term, fine scale prevalence data makes quantitative validation of the model impossible.
Although we expect our results to be qualitatively correct, we do not expect to be able to make quantitative comparisons with experimental data without further specializing the model.
The heterogeneity of the studies, mainly due to differences in gender, osteotomy techniques, and time of follow-up, made quantitative pooling of the data impossible and a systematic review represented the best available method to synthesize the current literature [ 30].
Only data sets based on expeditions and master projects (i.e. Macroben) made available quantitative data.
To date, however, full use has not been made of quantitative data for detection, characterization, or progression of visual field defects in ischemic optic neuropathy.
In contrast, physiologically-based mechanistic models can consider the scope and interplay of a range of physiological changes after food intake and, in combination with appropriate in vitro drug- and formulation-specific data, can make quantitative predictions of formulation-specific FE including the inter-individual variability of such effects.
Our integrative approach has made quantitative analysis of complex visual data possible.
