By Cobelli C., Carson E.
This unified modeling textbook for college kids of biomedical engineering offers a whole direction textual content at the foundations, conception and perform of modeling and simulation in body structure and drugs. it's devoted to the wishes of biomedical engineering and medical scholars, supported via utilized BME functions and examples. . constructed for biomedical engineering and similar classes, with an interdisciplinary clinical/engineering technique, quantitative foundation, and plenty of utilized examples to augment studying. supplies a quantitative method of modeling and in addition covers simulation. Case reviews and engineering functions from BME, plus finish of bankruptcy routines and Instructor's guide
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6 Autocorrelation function of the first differences of the urine potassium data (adapted from Flood and Carson, 1993). This example illustrates how ARIMA modeling can be used in ﬁtting time series data. In practice, however, this modeling approach can be difﬁcult when the number of data points is comparatively low. In this case there were 27 clinical data points. General experience is that a time series of at least 50–100 values is needed if the errors in estimating the parameters of the ARIMA model are not to be unacceptably large.
Having discussed these issues, we shall go on to discuss some of the ways in which data modeling can be performed. This will be done by means of a range of examples, considering the different ways in which physiological data can arise. 2 THE BASIS OF DATA MODELING Data modeling provides us with a means of representing the variables which characterize physiological dynamics as captured by the measurement process. A ﬁrst point to make is that these models are in essence ‘black box’ models and as such are mathematical representations of our measurement data, having only implicit correspondence to the underlying physiology that gives rise to these measures.
7 MODEL VALIDATION Validating a model is in essence examining whether it is good enough in relation to its intended purpose. 7 MODEL VALIDATION that it can reasonably be tested. A model is by deﬁnition an approximation of reality. As such, it will not be able to reproduce all the features of behavior that would be found in the real system. The question is can it reproduce those that matter in terms of how it is to be used in practice? When working with a number of competing, candidate models, the validation process consists of determining which of these models is best in relation to its intended purpose.
Introduction to modeling in physiology and medicine by Cobelli C., Carson E.