Interpretable multimodal learning for cardiovascular hemodynamics assessment.

This is a preprint and may not have undergone formal peer review

Tripathi, P.C., Tabakhi, S., Suvon, M.N.I. orcid.org/0000-0001-9962-315X et al. (5 more authors) (Submitted: 2024) Interpretable multimodal learning for cardiovascular hemodynamics assessment. [Preprint - arXiv] (Submitted)

Abstract

Metadata

Item Type: Preprint
Authors/Creators:
Copyright, Publisher and Additional Information:

© 2024 The Author(s). This preprint is made available under a Creative Commons Attribution 4.0 International License. (https://creativecommons.org/licenses/by/4.0/)

Keywords: Cardiac Hemodynamics; Feature Selection; Interpretable Model; Multimodal Learning; Pulmonary Arterial Wedge Pressure; Transformer
Dates:
  • Submitted: 6 April 2024
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Funding Information:
Funder
Grant number
WELLCOME TRUST (THE)
215799/Z/19/Z
Depositing User: Symplectic Sheffield
Date Deposited: 18 Oct 2024 14:48
Last Modified: 18 Oct 2024 14:48
Status: Submitted
Identification Number: 10.48550/arXiv.2404.04718
Related URLs:
Open Archives Initiative ID (OAI ID):

Download

Export

Statistics