ECG-LLM: Foundation Model for ECG-Based Cardiac Reasoning
Electrocardiography (ECG) is an inexpensive, standard-of-care test for cardiac symptoms, but front-line triage often lacks immediate access to definitive imaging such as echocardiography (ECHO) or cardiac magnetic resonance (CMR). Furthermore, most existing ECGAI systems are limited to fixed diagnostic labels or automated reports, constraining their use for patient-specific clinical reasoning. To address this gap, we introduce ECG-LLM, an ECG-conditioned large language model trained across four cohorts comprising 679,112 ECG studies from 186,409 patients. Using a novel multimodal-to-language supervision strategy, ECG-LLM is trained on clinically structured question-answer pairs derived fr...
| Authors | Alexander Selivanov, Friederike Jungmann, Jan Kehrer et al. |
|---|---|
| Primary category | eess.SP |
| Published | 15 July 2026 |
| Last updated at source | 15 July 2026 |
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