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Research1 min read
A new Latent-Attention Masked Autoencoder (LAMAE) was developed for learning patient-level representations from multimodal cardiac data. Pretrained on MIMIC-IV, LAMAE outperforms modality-specific models and achieves improved performance across multiple clinical tasks, even with single-modality inputs.
From arXiv cs.AI
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