… and performed seven-fold cross-validation on 11,652 chest radiographs (a subset of the
first … When deploying the trained model on the NIH dataset to the external dataset (Indiana …

… network architecture for normalcy detection in chest x-ray images. … and validated on a large
public dataset of frontal chest X-ray … This work reports one of the first experiences with deploy…

… the adoption of chest x-ray algorithms is that deployment requires … Most chest x-ray algorithms
are developed and validated on … validation and test set to be used for model validation and …

… Here, we develop and validate a deep learning-based model using routinely collected chest
… then transfer learning with k-fold cross-validation was used on a pre-trained ResNet50 deep …

… validate DLAD algorithm for detection of active pulmonary tuberculosis and any radiologically
identifiable relevant abnormality on chest radiographs … issues, we deployed the DLAD …

… This paper introduces a novel workflow for deploying the … of privately held and public
chest radiographs. In particular, we … this shift and experimentally validated its effectiveness in …

… Recent validation studies on commercial AI applications for chest … chest radiograph of a
20-year-old male patient with chest pain after a previous COVID-19 infection. The radiograph …

… DIANA uses Docker containerization to easily deploy AI solutions without customized … :1:2
train-validation-split on the CXRs from the 2011 Penn patients. Chest radiograph images from …

… digital x-rays, scaled deployment demands a solution that can … validation of deep
learning–based automatic detection algorithm for malignant pulmonary nodules on chest radiographs…

… CheXpert contains 224,316 chest radiographs of 65,240 … did out-of-sample external validations.
And further, only 14 of such … deployed and the degree of autonomy they should be given. …