… It should be noted when comparing our results to the current literature that only the study
by Keski-Filppula et al deployed the same algorithm as presented in our study. Differences in …

… , validation, and test sets. The DenseNet and MobileNetV2 CNN architectures were used to
train models on each dataset to classify chest radiographs … data before clinical deployment. A …

… presents the validation of the model on certain test images and shows that the model is
reliable to an extent. This paper also demonstrates a general architecture for the deployment of …

… Once deployed, all radiology reports collected within 24 … Some factors that need to be
considered before deploying our … However, we used both chest radiographs and CT scans as …

… CXRs and the external validation are advantages over … This study offers 2 potential clinical
deployment methods for … , as shown in internal validation and external validation data sets. In …

… diagnosis of their lung cancer via chest radiographs (CXR). This … cancers focus either on
deployment independent of radiologists, … This study has been designed to validate performance …

… web deployment of an inference model for Coronavirus COVID-19 using machine vision on
chest radiographs (… The model was further successfully validated on CXR images from an …

… Our dataset comprised 30 000 frontal view chest radiographs from the 112 000-image public
… of area in pixels of final bounding boxes in the test set and the training and validation set. …

… After the qXR was deployed ie, post-qXR, we obtained the … ] with comparable performance,
but validation of such tools in … in real clinical settings, a validation of its performance in the …

RATIONALE AND OBJECTIVES: The aim of the study is to measure the impact of a picture
archive and communication system (PACS) on dictation turnaround time of chest radiographs …