Table 3.
Performance of the AI model and clinicians in predicting the risk of breast cancer
| Sensitivity* | Specificity* | Accuracy (binary model) | Accuracy (multinomial model) | PPV* | NPV* | |
|---|---|---|---|---|---|---|
| AI model | 0.8451 | 0.8387 | 0.8627 | 0.7353 | 0.9231 | 0.7027 |
| Surgeons | ||||||
| Reader 1 | 0.8451 | 0.5484 | 0.7549 | 0.4510 | 0.8108 | 0.6071 |
| Reader 2 | 0.9437 | 0.6129 | 0.8431 | 0.6471 | 0.8481 | 0.8261 |
| Reader 3 | 0.9296 | 0.5484 | 0.8137 | 0.6176 | 0.8250 | 0.7727 |
| Average | 0.9061 | 0.5699 | 0.8039 | 0.5719 | 0.8280 | 0.7353 |
| Radiologists | ||||||
| Reader 4 | 0.8028 | 0.6129 | 0.7451 | 0.4608 | 0.8261 | 0.5758 |
| Reader 5 | 0.9437 | 0.6452 | 0.8529 | 0.6569 | 0.8590 | 0.8333 |
| Reader 6 | 0.9296 | 0.6452 | 0.8431 | 0.6569 | 0.8571 | 0.8000 |
| Average | 0.8920 | 0.6344 | 0.8137 | 0.5915 | 0.8474 | 0.7364 |
Abbreviations: AI, artificial intelligence; PPV, positive predictive value; NPV, negative predictive value.
*
for binary model.