The scope of the project is to develop and use computational intelligence methods for the prediction of mechanical responses to the pulsation in human blood vessels with an atherosclerotic plaque that could grow in a stochastic statement.

The project is planned to be organized into 4 work packages (WP):

• WP1. Development of a symbolic regression method for the identification of the mathematical model of the complex bio-material visco-elastic behavior based on the experimental data processing (based on data from literature)
• WP2. Development of a parametric computational model (based on FEM) for human blood vessels with an atherosclerotic plaque that allows making a statistical analysis of the possible mechanical response of vessels under different blood pressure pulsations depending on the patient’s medical conditions
• WP3. Development of ML-based model (Gauss stochastic regression approach, active learning Krigging) for the prognosis of the stochastic growth of the atherosclerotic plaque
• WP4. Prognosis of the statistical estimation for the mechanical responses of the human blood vessels that have some aged degradation and atherosclerotic affection that could be used for medical purposes

The basic methodology represented:

• the integration of the WP1 results into WP2 model
• WP2 one could recognize as the basic tool for the synthetic data generation for the WP3
• and the mutual integration of WP1-WP3 is the approach that is used in WP4 for the studies of some use cases and practical issues.

However, several WPs will be started and given in parallel by the different assigned investigators from the project team. It is proposed to start all the WPs with independent simplified models that will be interactively refined by the integration of the results obtained from different WPs during the project realization.

In principle, the project timeline will consist of 3 stages that iteratively refine the approach proposed in general methodology.

• The 1st stage (3 months) deals with the parallel development of the WP1, WP2, and WP3 by 2 team members each and assumed the development of the basic algorithms and solutions of benchmark problems
• The 2nd stage (5 months) deals with the usage of the obtained results within WP1
  in WP2 and WP2 in WP3. In this stage as an independent study will be provided the basic concept realization for the WP4 with direct usage of developed models (probably simplified) in WP2
• The 3rd stage (4 months) deals with the general integration of the outcomes of WP1-WP3 into the WP3, i.e. the computational intelligence methods for the statistical prediction of the blood vessels mechanical response considering the atherosclerotic plaque. The stage will be also focused on studying several cases of different types of atherosclerotic disease peculiarities as practical examples.