Uncertainty and sensitivity analysis of cardiovascular system - Gul, Raheem
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Cardiovascular disease is one of the leading causes of death in the world and the number of patients increases worldwide. To investigate the cardiovascular disease in early stage, reliable model predictions are required. In computational cardiovascular models parameters are one of the major sources of uncertainty, which make the models unreliable and less predictive. In order to achieve predictive models that allow the investigations of the cardiovascular diseases, sensitivity analysis (SA) can be used to quantify and reduce the output uncertainty caused by model parameters.

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Produktbeschreibung
Cardiovascular disease is one of the leading causes of death in the world and the number of patients increases worldwide. To investigate the cardiovascular disease in early stage, reliable model predictions are required. In computational cardiovascular models parameters are one of the major sources of uncertainty, which make the models unreliable and less predictive. In order to achieve predictive models that allow the investigations of the cardiovascular diseases, sensitivity analysis (SA) can be used to quantify and reduce the output uncertainty caused by model parameters.
Autorenporträt
Dr. Raheem Gul was born in Abbottabad, K.P.K, Pakistan. Mr. Gul successfully completed his PhD degree from Free University Berlin in 2016. Currently, he is teaching mathematics to graduate and undergraduate level students at COMSATS Abbottabad. His main interests are modeling cardiovascular system in 0D and sensitivity analysis (local and global).