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Multimodal Autoencoder for Cardiac Instability by larrylynnmail is a document available to read on EtoBox.

What is Multimodal Autoencoder for Cardiac Instability about?

1) The document proposes a novel multimodal variational autoencoder (CardioVAEX,G) to integrate low-cost chest X-ray (CXR) and electrocardiogram (ECG) data to detect cardiac hemodynamic instability (CHDI). 2) CardioVAEX,G is first pre-trained on a large unlabeled dataset of CXR and ECG data to learn shared and modality-specific features, then fine-tuned on a smaller labeled dataset to predict pulmonary artery wedge pressure (PAWP) and detect CHDI. 3) Experimental results show CardioVAEX,G achieves promisi

Author

larrylynnmail

Language

EN