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Interpretable Multimodal Learning for Cardiovascular Hemodynamics Assessment
April 9, 2024, 4:46 a.m. | Prasun C Tripathi, Sina Tabakhi, Mohammod N I Suvon, Lawrence Sch\"ob, Samer Alabed, Andrew J Swift, Shuo Zhou, Haiping Lu
cs.CV updates on arXiv.org arxiv.org
Abstract: Pulmonary Arterial Wedge Pressure (PAWP) is an essential cardiovascular hemodynamics marker to detect heart failure. In clinical practice, Right Heart Catheterization is considered a gold standard for assessing cardiac hemodynamics while non-invasive methods are often needed to screen high-risk patients from a large population. In this paper, we propose a multimodal learning pipeline to predict PAWP marker. We utilize complementary information from Cardiac Magnetic Resonance Imaging (CMR) scans (short-axis and four-chamber) and Electronic Health Records …
arxiv assessment cs.ai cs.cv multimodal multimodal learning type
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