Bayesian inference of multi-sensors impedance cardiography for detection of aortic dissection

  title={Bayesian inference of multi-sensors impedance cardiography for detection of aortic dissection},
  author={Vahid Badeli and Sascha Ranftl and Gian Marco Melito and Alice Reinbacher-K{\"o}stinger and Wolfgang von der Linden and Katrin Ellermann and Oszk{\'a}r B{\'i}r{\'o}},
  journal={COMPEL - The international journal for computation and mathematics in electrical and electronic engineering},
  • V. BadeliSascha Ranftl O. Bíró
  • Published 21 December 2021
  • Medicine
  • COMPEL - The international journal for computation and mathematics in electrical and electronic engineering
Purpose This paper aims to introduce a non-invasive and convenient method to detect a life-threatening disease called aortic dissection. A Bayesian inference based on enhanced multi-sensors impedance cardiography (ICG) method has been applied to classify signals from healthy and sick patients. Design/methodology/approach A 3D numerical model consisting of simplified organ geometries is used to simulate the electrical impedance changes in the ICG-relevant domain of the human torso. The… 
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