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_29
Snippet: Filtering only the good signal recordings, we directly compared prediction to clinically defined ground truth in the confusion matrix in Table 2 . Algorithm performance had a sensitivity and specificity for detecting murmurs of 76.3% (95% CI: 72.9-79.3%) and 91.4% (95% CI: 89.6-93.1%), respectively (Table 3) , and a positive predictive value of 86.6% (95% CI: 84.0-89.3%) using the murmur prevalence from this test set. The likelihood ratios positi.....
Document: Filtering only the good signal recordings, we directly compared prediction to clinically defined ground truth in the confusion matrix in Table 2 . Algorithm performance had a sensitivity and specificity for detecting murmurs of 76.3% (95% CI: 72.9-79.3%) and 91.4% (95% CI: 89.6-93.1%), respectively (Table 3) , and a positive predictive value of 86.6% (95% CI: 84.0-89.3%) using the murmur prevalence from this test set. The likelihood ratios positive and negative are 8.89 (95% CI: 7.35-11.08) and 0.259 (95% CI: 0.225-0.297), respectively (Table 3) .
Search related documents:
Co phrase search for related documents- Algorithm performance and ground truth: 1, 2, 3, 4, 5, 6, 7, 8
- Algorithm performance and predictive value: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
- Algorithm performance and specificity sensitivity: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34
- Algorithm performance and test set: 1, 2, 3, 4, 5, 6, 7
- confusion matrix and predictive value: 1
- confusion matrix and specificity sensitivity: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21
- confusion matrix and test set: 1, 2, 3, 4, 5, 6, 7
- ground truth and prediction compare: 1, 2
- ground truth and predictive value: 1, 2, 3, 4
- ground truth and specificity sensitivity: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18
- ground truth and test set: 1, 2, 3, 4, 5, 6, 7, 8, 9
- likelihood negative positive ratio and negative positive ratio: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68
- likelihood negative positive ratio and predictive value: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22
- likelihood negative positive ratio and specificity sensitivity: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63
- likelihood negative positive ratio and test set: 1, 2
- negative positive ratio and predictive value: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24
- negative positive ratio and specificity sensitivity: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69
- negative positive ratio and test set: 1, 2
- prediction compare and specificity sensitivity: 1, 2, 3, 4, 5, 6
Co phrase search for related documents, hyperlinks ordered by date