A frame-wise masked autoencoder with a temporal contrastive loss achieves 0.88 AUROC for binary EF classification on EchoNet-Dynamic, below the cited 0.93 AUROC of ECHO-VISION-FM.
Title resolution pending
1 Pith paper cite this work, alongside 29 external citations. Polarity classification is still indexing.
1
Pith paper citing it
29
external citations · OpenAlex
citation-role summary
background 1
citation-polarity summary
fields
eess.IV 1years
2025 1verdicts
REJECT 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Temporal Representation Learning for Real-Time Ultrasound Analysis
A frame-wise masked autoencoder with a temporal contrastive loss achieves 0.88 AUROC for binary EF classification on EchoNet-Dynamic, below the cited 0.93 AUROC of ECHO-VISION-FM.