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A deep neural network learning algorithm outperforms a conventional algorithm for emergency department electrocardiogram interpretation - ScienceDirect

Cardiologs® vs. Veritas® accuracy for finding a major abnormality was 92.2% vs. 87.2% (p < 0.0001), with comparable sensitivity (88.7% vs. 92.0%, p = 0.086), improved specificity (94.0% vs. 84.7%, p < 0.0001) and improved positive predictive value (PPV 88.2% vs. 75.4%, p < 0.0001). Cardiologs® had accurate ECG interpretation for 72.0% (95% CI: 69.6–74.2) of ECGs vs. 59.8% (57.3–62.3) for Veritas® (P < 0.0001). Sensitivity for any abnormal group for Cardiologs® and Veritas®, respectively, was 69.6% (95CI 66.7–72.3) vs. 68.3% (95CI 65.3–71.1) (NS). Positive Predictive Value was 74.0% (71.1–76.7) for Cardiologs® vs. 56.5% (53.7–59.3) for Veritas® (P < 0.0001).