AI RESEARCH
Fine-tuning an ECG Foundation Model to Predict Coronary CT Angiography Outcomes
arXiv CS.CV
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ArXi:2512.05136v3 Announce Type: replace CAD remains a major global public health burden, yet scalable screening tools are limited. Although CCTA is a first-line non-invasive diagnostic modality, its use is constrained by resource requirements and radiation exposure. AI-ECG may offer a complementary approach for CAD risk stratification. In this multicenter study, we developed and validated an AI-ECG model using CCTA as the anatomical reference standard to predict vessel-specific coronary stenosis.