2009
DOI: 10.15388/informatica.2009.265
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Digital Model of Blood Circulation Analysis System

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Cited by 8 publications
(3 citation statements)
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“…representing the probability that a patient is in state j of the disease at the (n + 1)th transition within chronological time t, given that at the nth transition she/he entered state i at time s being aged a + s. In such a way the model is able to consider transition probabilities taking into account both the patient's age and the medical scientific progress due to the chronological time effect. The medical scientific progress are due to the creation of diagnostic medicine systems, see for example Maciulis et al (2009). The dependence of the transition rates on the age of the patient is considered using a semi-Markov model with age index.…”
Section: Age-time Dependence Stochastic Modelmentioning
confidence: 99%
“…representing the probability that a patient is in state j of the disease at the (n + 1)th transition within chronological time t, given that at the nth transition she/he entered state i at time s being aged a + s. In such a way the model is able to consider transition probabilities taking into account both the patient's age and the medical scientific progress due to the chronological time effect. The medical scientific progress are due to the creation of diagnostic medicine systems, see for example Maciulis et al (2009). The dependence of the transition rates on the age of the patient is considered using a semi-Markov model with age index.…”
Section: Age-time Dependence Stochastic Modelmentioning
confidence: 99%
“…This phenomenon is not very common in standard time-delay systems where delays do not play usually a relevant role in the parameterizations but only in the state-trajectory solution through the delayed state dynamics (De la Sen, 2003; De la Sen and Luo, 2004;Luo et al, 1997). It has to be pointed out that the use of mathematical models supported by electronics instrumentation is also very relevant for the study of biological process such as models of blood circulation because of its facility for discretized implementation of real testing experiments (see, for instance, Maciulis et al, 2009). It has also to be pointed out that epidemic models are not controllable in the sense that all the populations cannot be simultaneously governed (Nieto and Tisdell, 2010).…”
Section: Introductionmentioning
confidence: 99%
“…During coronary artery bypass grafting operations a surgeon requires information regarding the coronary flow, coronary anatomy, and myocardial perfusion. Additional quantitative flow estimation is desirable to detect graft failures as early as possible (Mačiulis et al, 2009). Some pictures taken from the thermovisual video stream are presented in Fig.…”
Section: Introductionmentioning
confidence: 99%