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

<p dir="ltr">Software and data for PhD thesis of Juliet Nagawa</p><p dir="ltr"><b>FEM Models.zip </b></p><ul><li>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.</li><li>Refer to thesis chapters 2 and 3.</li></ul><p dir="ltr"><b>FEM Strain and stress.zip</b></p><ul><li>Myocardial strain and stress results from FEM models.</li><li>Refer to thesis chapters 2 and 3.</li></ul><p dir="ltr"><b>FEM Volume and pressure.zip</b></p><ul><li>Ventricular volume and pressure parameters from FEM models.</li><li>Refer to thesis chapters 2 and 3.</li></ul><p dir="ltr"><b>Statistical analysis.zip</b></p><ul><li>Matlab and R files for statistical analysis of PPCM demographics and cardiac function dataset</li><li>Refer to thesis chapter 4, sections 4.2.2.</li></ul><p dir="ltr"> <b>ANN.zip</b></p><ul><li>Matlab and Python programs used to develop machine learning algorithms and developed machine learning models.</li><li>Refer to thesis chapter 4, sections 4.2.3 and 4.2.4.</li></ul><p dir="ltr">Each archive file contains more detailed descriptions of the content as text files.</p>