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