A unified 12-lead ECG-language model for interpretation and clinical-endpoint prediction
DeepECG-Tok is presented, which reframes ECG interpretation as a unified instruction-following problem and establishes discrete ECG tokenization as a foundation for general-purpose models that generate clinically useful interpretations and answer diverse questions directly from cardiac waveforms.