Measures of Diagnostic Accuracy for AI Models for Cardiomyopathy Detection Based on Standard 12-Lead ECG and Digital Stethoscope Recordings
| na | AUC (95% CI) | Sensitivity, % (95% CI) | Specificity, % (95% CI) | Accuracy, % (95% CI) | F1 score | Negative predictive value, % (95% CI) | Odds ratio | Positive predictive value, % (95% CI) | |
|---|---|---|---|---|---|---|---|---|---|
| 12-lead ECG (LVEF <50%) | |||||||||
| AI-ECG | 100 | 0.939 (0.883-0.995) | 40.0 (5.3-85.3) | 95.8 (89.6-98.8) | 93.0 (86.1-97.1) | 36.4 | 96.8 (91.0-99.3) | 15.2 (2.0-117.9) | 33.3 (4.3-77.7) |
| Digital stethoscope ECG + PCG (LVEF < 50%) | |||||||||
| Angled | 99 | 0.983 (0.955-1.000) | 80.0 (28.4-99.5) | 93.6 (86.6-97.6) | 92.9 (86.0-97.1) | 53.3 | 98.9 (93.9-100.0) | 58.7 (5.6-610.4) | 40.0 (12.2-73.8) |
| Subclavicular | 96 | 0.857 (0.672-1.000) | 60.0 (14.7-94.7) | 90.1 (82.1-95.4) | 88.5 (80.4-94.1) | 35.3 | 97.6 (91.7-99.7) | 13.7 (2.0-92.9) | 25.0 (5.5-57.2) |
| V2 | 100 | 0.949 (0.871-1.000) | 80.0 (28.4-99.5) | 91.6 (84.1-96.3) | 91.0 (83.6-95.8) | 47.1 | 98.9 (93.8-100.0) | 43.5 (4.3-437.3) | 33.3 (9.9-65.1) |
| Mean prediction | 100 | 0.971 (0.929-1.000) | 60.0 (14.7-94.7) | 93.7 (86.8-97.6) | 92.0 (84.8-96.5) | 42.9 | 97.8 (92.3-99.7) | 22.2 (3.1-159.7) | 33.3 (7.5-70.1) |
| Maximum prediction | 100 | 0.979 (0.950-1.000) | 100.0 (47.8-100.0) | 82.1 (72.9-89.2) | 83.0 (74.2-89.8) | 37.0 | 100.0 (95.4-100.0) | 49.3 (2.6-934.3) | 22.7 (7.8-45.4) |
AI = artificial intelligence; AUC = area under the curve; ECG = electrocardiography; LVEF = left ventricular ejection fraction; PCG = phonocardiogram.
↵a Results shown represent available AI prediction results based on diagnostic-quality ECG/phonocardiography. Missing or recorded ECG/phonocardiography data deemed to be of poor quality were excluded from analysis, resulting in a sample size <100 for some of the digital stethoscope recording locations.