Stanford: AI reads routine ECGs to flag sudden cardiac death risk in 86% with no known warning signs
oziadias · x · 2026-10-31
At Stanford Medicine Grand Rounds, oziadias presented how an AI model reads routine ECGs to identify people at high risk of sudden cardiac death.
Key finding: 86% of the flagged individuals had never been diagnosed with the low ejection fraction that normally qualifies someone for a defibrillator — meaning current clinical criteria would have completely missed them.
The talk explored what the model picked up in ECG waveforms, suggesting routine ECGs contain sudden-death warning signals that existing guidelines fail to exploit.
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