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1 Burden of Diabetes Type 2 Through Modelling and Simulation
| Content Provider | Semantic Scholar |
|---|---|
| Author | Atanasijevi, Maja Kunc Drinovec, Joze |
| Copyright Year | 2012 |
| Abstract | Modelling and simulation represent well established approaches when analyzing systems’ properties, their behaviour, predicting possible scenarios, or estimating potential results or responses when influencing the observed system (Cellier, 1991; Cassandras & Lafortune, 1999; Cellier & Kofman, 2006; D'Inverno & Luck, 2010). Such knowledge organization about a given problem can help in its presentation, understanding, explanation and it is also frequently used through system design (Matko et al., 1992). Modelling and model usage can be classified and/or chosen as methodology regarding different criteria which can in addition be interdependent due to important activities needed in such situations. Criteria can represent the way of data collecting, their form and degree of confidence, model structure and possibilities of model experimentations, the level of problem abstraction and its aggregation, the selection of time granulation, etc. One of the most important aspect (in spite of the fact that it is often not mentioned) which has to be taken into account, is also the goal of modelling which should lead the designer through the whole procedure of model development, its interpretation and experimentation. The last two facts are very important also for the user of developed model. This is perhaps also one of important reasons why very different mathematical approaches and descriptions are used, where the disciplines like medicine, pharmacy and the life sciences are no exception (Hoppensteadt & Peskin, 2002; Atanasijević-Kunc et al., 2008a; Stahl, 2008; Belič, 2009; Arnold 2010). This is true even in the cases where the same problem, like certain disease development (diabetes for example) is observed. Here the following questions can arise: Which presented or known model regarding certain problem (disease) is the most important or relevant one? Should this model be chosen in all situations? Can different modelling structures, descriptions or approaches predict the same or very similar results? When there is a need to develop a new approach or problem description? Is it possible to benefit from the usage of several different descriptions of the same problem? If the answer to the previous question is positive, it can be important also to find out, how different descriptions or models can share their results and/or complement each other? |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://api.intechopen.com/chapter/pdf-download/22092 |
| Alternate Webpage(s) | http://cdn.intechweb.org/pdfs/22092.pdf |
| Alternate Webpage(s) | http://cdn.intechopen.com/pdfs-wm/22092.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
