AI RESEARCH
CAMEL: An ECG Language Model for Forecasting Cardiac Events
arXiv CS.LG
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ArXi:2602.15677v3 Announce Type: replace Electrocardiograms (ECG) are electrical recordings of the heart that are critical for diagnosing cardiovascular conditions. ECG language models (ELMs) have recently emerged as a promising framework for ECG classification accompanied by report generation. However, current models cannot forecast future cardiac events despite the immense clinical value for planning earlier intervention. To address this gap, we propose CAMEL, the first ELM that is capable of inference over longer signal durations which enables its forecasting capability.