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An AI model trained on over 440,000 ECGs can identify sudden cardiac death risk far better than standard clinical tests, flagging a high-risk group with a 7% annual death rate versus 4.6% under current methods. That gap represents thousands of preventable deaths every year among people who look perfectly healthy by today's standards. This breakthrough could finally tell doctors who actually needs an implantable defibrillator before it's too late.
Powerful medical AI means nothing if patients can't trust how their data gets used — and it took a decade to compile the records behind this study, which shows just how murky the data pipeline really is. Hospitals, researchers and AI companies need clear guardrails before more health records get swept into training models. Better prediction can save lives, but trust will determine whether people ever accept these tools in the first place.