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Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics

Ph.D. thesis
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Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics

Summary

Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics is a doctoral thesis[1].

Key Facts

  • Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics authored Francesco Regazzoni[2].
  • Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics's instance of is recorded as doctoral thesis[3].
  • Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics's publisher is recorded as Polytechnic University of Milan[4].
  • Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics's place of publication is recorded as Milan[5].
  • Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics's language of work or name is recorded as English[6].
  • Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics's country of origin is recorded as Italy[7].
  • Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics's publication date is recorded as +2020-02-18T00:00:00Z[8].
  • Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics's work available at URL is recorded as https://www.politesi.polimi.it/bitstream/10589/152617/1/regazzoni_phd_thesis.pdf[9].
  • Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics's Handle ID is recorded as 10589/152617[10].
  • Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics's title is recorded as Mathematical Modeling and Machine Learning for the Numerical Simulation of Cardiac Electromechanics[11].
  • Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics's Google Scholar paper ID is recorded as 12109222514023339645[12].
  • Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics's thesis submitted to is recorded as Polytechnic University of Milan[13].

Body

Designation and Status

Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics's instance of is recorded as doctoral thesis[3].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [3] ↑ . wikidata.org.
  2. [2] ↑ . wikidata.org.
  3. [4] ↑ . wikidata.org.
  4. [5] ↑ . wikidata.org.
  5. [6] ↑ . wikidata.org.
  6. [7] ↑ . wikidata.org.
  7. [8] ↑ . wikidata.org.
  8. [9] ↑ . wikidata.org.
  9. [10] ↑ . wikidata.org.
  10. [11] ↑ . wikidata.org.
  11. [12] ↑ . wikidata.org.
  12. [13] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics. Retrieved May 3, 2026, from https://4ort.xyz/entity/mathematical-modeling-and-machine-learning-for-the-numerical-simulation-of-cardiac-electromechanics
MLA “Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics.” 4ort.xyz Knowledge Graph, 4ort.xyz, 3 May. 2026, https://4ort.xyz/entity/mathematical-modeling-and-machine-learning-for-the-numerical-simulation-of-cardiac-electromechanics.
BibTeX @misc{4ortxyz_mathematical-modeling-and-machine-learning-for-the-numerical-simulation-of-cardiac-electromechanics_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Mathematical modeling and machine learning for the numerical simulation of cardiac electromechanics}}, year = {2026}, url = {https://4ort.xyz/entity/mathematical-modeling-and-machine-learning-for-the-numerical-simulation-of-cardiac-electromechanics}, note = {Accessed: 2026-05-03}}
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