Deep learning-based detection system for multiclass lesions on chest radiographs: comparison with observer readings

To investigate the feasibility of a deep learning–based detection (DLD) system for multiclass lesions on chest radiograph, in comparison with observers. A total of 15,809 chest radiographs were collected from two tertiary hospitals (7204 normal and 8605 abnormal with nodule/mass, interstitial opacity, pleural effusion, or pneumothorax). Except for the test set (100 normal and 100 abnormal (nodule/mass, 70; interstitial opacity, 10; pleural...