Abstract: A system, comprising at least one cardiac sensor adapted to measure a hemodynamic profile of a patient; and a computing node operatively coupled to the cardiac sensor and configured to perform the steps of reading a hemodynamic profile of a patient; based on the hemodynamic profile, tuning a plurality of parameters of a cardiovascular model to create a digital twin of the patient; augmenting the hemodynamic profile of the patient with at least one parameter generated from the digital twin; providing the augmented hemodynamic profile to a pretrained machine learning model and receiving therefrom a patient profile; and outputting the patient profile for clinical decision support.

Abstract: A model of flow through a left ventricular assist device (LVAD) can be used for preoperative planning of implantation of the LVAD into a patient and/or optimization of the LVAD after implantation into the patient are described. At least one imaging data set related to a patient and at least one physiological data set related to the patient can be received. An ideal parameter related to the LVAD can be determined based on the at least one imaging data set related to the patient, the at least one physiological data set related to the patient using a model of circulation in a large spatial region of the patient's body and a three-dimensional anatomical model of at least one component of the region of the patient's body and at least one component of the LVAD. Flow patterns within the three-dimensional anatomical model are calculated using computational fluid dynamics.

Abstract: A model of flow through a left ventricular assist device (LVAD) can be used for preoperative planning of implantation of the LVAD into a patient and/or optimization of the LVAD after implantation into the patient are described. At least one imaging data set related to a patient and at least one physiological data set related to the patient can be received. An ideal parameter related to the LVAD can be determined based on the at least one imaging data set related to the patient, the at least one physiological data set related to the patient using a model of circulation in a large spatial region of the patient's body and a three-dimensional anatomical model of at least one component of the region of the patient's body and at least one component of the LVAD. Flow patterns within the three-dimensional anatomical model are calculated using computational fluid dynamics.