Multimodal Variational Autoencoder for Low-cost Cardiac Hemodynamics Instability Detection

arXiv:2403.13658v1 Announce Type: new
Abstract: Recent advancements in non-invasive detection of cardiac hemodynamic instability (CHDI) primarily focus on applying machine learning techniques to a single data modality, e.g. cardiac magnetic resonance imaging (MRI). Despite their potential, these approaches often fall short especially when the size of labeled patient data is limited, a common challenge in the medical domain. Furthermore, only a few studies have explored multimodal methods to study CHDI, which mostly rely on costly modalities such as cardiac MRI …

abstract arxiv autoencoder cost cs.cv cs.lg data detection focus imaging low machine machine learning machine learning techniques mri multimodal patient type