Author: John S Chorba; Avi M Shapiro; Le Le; John Maidens; John Prince; Steve Pham; Mia M Kanzawa; Daniel N Barbosa; Brent E White; Jason Paek; Sophie G Fuller; Grant W Stalker; Sara A Bravo; Dina Jean; Subramaniam Venkatraman; Patrick M McCarthy; James D Thomas
Title: A Deep Learning Algorithm for Automated Cardiac Murmur Detection Via a Digital Stethoscope Platform Document date: 2020_4_3
ID: fogzjrk2_36
Snippet: Allowing the algorithm's positive-negative decision boundary to vary, we can plot a receiver operating characteristic (ROC) curve to show different sensitivity and specificity tradeoffs. The FDA-cleared murmur detection algorithm, however, operates at a single point on this ROC curve, with performance described above. Figure 2 shows this ROC curve with the operating point of Eko software overlaid. Stratification of the ROC curve based on grade of.....
Document: Allowing the algorithm's positive-negative decision boundary to vary, we can plot a receiver operating characteristic (ROC) curve to show different sensitivity and specificity tradeoffs. The FDA-cleared murmur detection algorithm, however, operates at a single point on this ROC curve, with performance described above. Figure 2 shows this ROC curve with the operating point of Eko software overlaid. Stratification of the ROC curve based on grade of the murmur again shows that the detection algorithm operates with significantly improved characteristics with a higher grade murmur (Fig. 2, green line) .
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