… Tertiary ICU’s typically generate over 250 chest radiographs per day to confirm tube … (CAD)
system for tube detection on bedside chest radiographs. The CAD system is based on …

… In this work, we present CheXpert (Chest eXpert), a large dataset for chest radiograph …
chest radiographs of 65,240 patients labeled for the presence of 14 common chest radiographic …

… to be detected by the system. Therefore, the evaluation could … chest radiographs as well as
abnormal chest radiographs may … system demonstrated a high possibility to detect and label …

… the view position of chest radiographs is embedded in a system for content-based image
retrieval in medical applications (IRMA).8 IRMA is a distributed system using a central relational …

… Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison.
In Proceedings of the AAAI Conference on Artificial Intelligence, Honolulu, HI, USA, 27 …

… Chest radiography is a common imaging modality used to assess the thorax and the most
common medical imaging study in the world. Chest radiographs … analysis of radiographs has …

… to the label noise. Furthermore, we exploit the high comorbidity of abnormalities observed
in chest radiography and incorporate this information to further reduce the impact of label noise…

… To demonstrate wide coverage of all fine-grained findings found in AP chest radiographs
, we collected datasets from 3 separate sources, namely, the MIMIC-4 6 , a dataset of over …

… labeled chest radiographs achieved high diagnostic performance in the classification of chest
radiographs as normal … labeled chest radiographs show promise in performing automated …

… labeled radiographs to predict the clinical priority from radiologic appearances only. The
system’s performance in radiograph … set of 15 887 radiographs. Prediction performance was …