Automated identification of chest radiographs with referable abnormality with deep learning: need for recalibration.

• A deep learning model tended to overestimate the likelihood of the presence of abnormalities in chest radiographs. • Simple recalibration of the deep learning model using output scores could improve the calibration of model while maintaining discrimination. • Improved calibration of a deep learning model may enhance the interpretability and the credibility of the model for users.