Triplicate Training and Validation Binary Results (Hyperthyroid or Not Hyperthyroid) for 30-Layer CNN Architecture
| Input tensor | Training accuracy | Training loss | Validation accuracy | Validation loss | Mean validation accuracy | Binary accuracy |
|---|---|---|---|---|---|---|
| White on black | 82.1% | 0.420 | 75.9% | 0.536 | 80.5% | |
| 94.0% | 0.225 | 79.3% | 0.602 | |||
| 91.0% | 0.218 | 86.2% | 0.414 | |||
| Black on white | 83.6% | 0.383 | 82.8% | 0.405 | 78.2% | |
| 80.6% | 0.452 | 72.4% | 0.544 | |||
| 91.0% | 0.232 | 79.3% | 0.690 | |||
| Magnitude spectrum | 76.1% | 0.459 | 75.9% | 0.530 | 75.9% | |
| 74.6% | 0.508 | 72.4% | 0.542 | |||
| 85.1% | 0.306 | 79.3% | 0.380 | |||
| Mean | 84.2% | 0.356 | 78.2% | 0.516 | ||
| Initial 25-layer CNN | 69.0% | |||||
| Conventional metrics | ||||||
| Normal cutoff, 4.5% | 82.6% | |||||
| Normal cutoff, 4.0% | 77.1% | |||||
| Salivary classification | 61.5% | |||||
| Physician rating | 61.0% | |||||
| Physician rating with uptake | 82.3% |
Corresponding binary accuracies of best-performing thyroid uptake cutoffs, visual classification against salivary activity relative to thyroid activity, and physician rating are included for comparison.