Article

Graph-Enhanced Cross-Domain Robust Contrastive Learning for Noisy and Disparate Medical Time Series Analysis

2025-12-23

Abstract excerpt

Medical time series data, such as electroencephalograms and electrocardiograms, are vital for diagnosis but face challenges from noise, cross-domain variability, and limited labeled data. Traditional and existing contrastive learning methods often struggle to yield robust and generalizable models. We propose Graph-Enhanced Cross-domain Robust Contrastive Learning (GCRoCL), a novel framework for learning noise-robu...

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Literature Corpus work: dc36c17b-e79f-5a02-9998-e16715fa6f1d
DOI: 10.20944/preprints202512.2041.v1

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