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Investigation of cardiac mechanics and mechanical circulatory support therapies in peripartum cardiomyopathy using machine learning and patient-specific computational modelling

dataset
posted on 2023-11-06, 08:29 authored by Juliet NagawaJuliet Nagawa, Kevin Sack, Sarah Kraus, Mazin Sirry, Ntobeko AB Ntusi, Sliwa, Karen, Neil DaviesNeil Davies, Thomas FranzThomas Franz

Software and data for PhD thesis of Juliet Nagawa

FEM Models.zip

  • Biventricular cardiac model input files (Abaqus, Dassault Systèmes, Providence, USA) of six PPCM patients to simulate five cardiac cycles (active contraction and passive filling). Six models per patient: No LVAD support, LVAD support with speeds of 8k to 12k.
  • Refer to thesis chapters 2 and 3.

FEM Strain and stress.zip

  • Myocardial strain and stress results from FEM models.
  • Refer to thesis chapters 2 and 3.

FEM Volume and pressure.zip

  • Ventricular volume and pressure parameters from FEM models.
  • Refer to thesis chapters 2 and 3.

Statistical analysis.zip

  • Matlab and R files for statistical analysis of PPCM demographics and cardiac function dataset
  • Refer to thesis chapter 4, sections 4.2.2.

ANN.zip

  • Matlab and Python programs used to develop machine learning algorithms and developed machine learning models.
  • Refer to thesis chapter 4, sections 4.2.3 and 4.2.4.

Each archive file contains more detailed descriptions of the content as text files.

Funding

Dr. Leopold und Carmen Ellinger Stiftung

German Academic Exchange Service (DAAD)

African Institute for Mathematical Sciences

History

Department/Unit

Biomedical Engineering Research Centre Department of Human Biology University of Cape Town