Prediction of radiographic abnormalities by the use of bag-of-features and convolutional neural networks

The accuracy of both models ranged from 79.6% to 96.9% in the testing set. CNN showed higher accuracy (CNN; 92.9-96.9% and BOF; 79.6-96.9%) and sensitivity (CNN; 92.1-100% and BOF; 74.1-94.8%) than BOF. In conclusion, both BOF and CNN have potential to be useful for improving work efficiency by double reading.