Selected article for: "detection algorithm and ROC curve"
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_40
    Snippet: We are also able to screen for mitral regurgitation (MR) with the murmur detection algorithm. Using the same patient cohort, and the same inclusion and exclusion criteria as for aortic stenosis, except testing at the single mitral/apex location, we have 32 cases and 84 controls. There are fewer control subjects for MR because there are a greater number of 'poor signal' recordings at the mitral position. The ROC curve is presented in Figure 5 . Th.....
    Document: We are also able to screen for mitral regurgitation (MR) with the murmur detection algorithm. Using the same patient cohort, and the same inclusion and exclusion criteria as for aortic stenosis, except testing at the single mitral/apex location, we have 32 cases and 84 controls. There are fewer control subjects for MR because there are a greater number of 'poor signal' recordings at the mitral position. The ROC curve is presented in Figure 5 . The algorithm compares favorably to the annotators, whose performances fall along the ROC curve. Performance metrics with confidence intervals are given in Table 8 .

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