… ) compared chest radiographs, radiology reports, … -deployment external validation. When
not performed, models fail to generalize, creating risk for healthcare providers looking to deploy …

… A chest radiograph is upright if the di®… validate our method on sets of normal and abnormal
images and argue that rib orientation can be used for rotation detection in chest radiographs …

… clinical deployment of AI systems in radiology. We aimed to contribute an AI system for
comprehensive chest x-… Simplified transfer learning for chest radiography models using less data. …

… This phenomenon is well known in DL research (29) and precludes the safe deployment of
developed DL algorithms without extensive validation on new data sets (30). Fine-tuning our …

… The chest algorithms deployed retrospectively were a useful quality tool and AI augmented
… It is important to account for prevalence of these chest conditions in clinical context and use …

… In this retrospective study, 22 960 de-identified frontal chest radiographs from 11 153
patients (average age, 60.2 years ± 19.9 [standard deviation], 55.6% men) between 2010 and …

… Post-deployment measures taken to improve the NPV … % for classifying normal versus
abnormal chest radiographs.… a validation study, setting the ground truth in post-deployment …

… While chest radiograph (CXR) is the first-line imaging … We developed and validated an AI
system for COVID-19 … , trained on 168,850 CXRs, was validated on a large international test set …

… detecting tuberculosis in conventional posteroanterior chest radiographs. We first extract the
… screening, which is ready for field deployment, achieves a performance that approaches the …

… When deployed for radiographs retrieved … validation dataset size through augmentation
techniques (although we applied standard image augmentation during training and validation). …