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Despite its importance, however, to our knowledge there are no published in silico models to simulate the progression of discrete virtual projects through a discovery milestone system.
A decision analytic model and Markov modeling techniques previously designed [14] were used to simulate the progression of a hypothetical cohort of 1,000 Spanish patients who are initially not on dialysis, representing the relevant stages of the natural history of the disease over time, as well as estimates for probability of progression between the health states related to CKD.
Although a number of simulation and game theory algorithms have been used in clinical development models, [7] to our knowledge there are no published in silico models that simulate the progression of projects through early discovery, i.e. from conceptualization to candidate selection.
Transitions in the model simulate the progression of COPD, exacerbations, and death.
The ordinary differential equation-based model was used to simulate the progression of sepsis over a 30-day hospital stay.
Such models are needed to construct computer models to simulate the progression of diabetes, and may, with further validation, be useful for clinical decision making.
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Thus, this model fails to simulate the progression to NASH.
The model successfully simulates the progression of healing and predicts that the rate of osteogenic growth factor production by osteoblasts and the duration of the initial release of growth factors upon injury are particularly important parameters for complete ossification and successful healing.
Also, the model simulates the progression of diabetes under "conventional treatment" within the UKPDS study.
The model simulated the progression of patients from the moment they start therapy to various different states during treatment cycles.
The model simulates the progression of diabetes and accompanying complications for a cohort of subjects with type 2 diabetes.
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