New research confirms that an artificial intelligence (AI) model trained on millions of electrocardiograms (ECGs) serves as a novel, robust, and independent predictor of postoperative atrial fibrillation (AF) following cardiac surgery. It provides additive or synergistic predictive value when integrated with existing postoperative AF prediction tools or other risk factors. The AI-enhanced model significantly improves the accuracy of existing prediction tools, acting as a noninvasive biomarker for preoperative risk stratification for postoperative AF prediction in cardiac surgery patients, potentially enabling healthcare providers to initiate tailored prophylactic therapy and implement targeted monitoring during the perioperative period.

These findings were published in the November issue

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