MS-ECG-FM: Towards a More Universal Electrocardiogram Foundation Model for Health Monitoring using Multi-source Contrastive Learning
MS-ECG-FM is a new ECG foundation model trained using multi-source contrastive learning across diverse clinical notes like discharge reports and radiology images. It outperforms existing models by capturing complementary diagnostic information, leading to better detection of a wider range of heart conditions, even in reduced-lead settings.