S Jang, H Song, YJ Shin, J Kim, J Kim, KW Lee, SS Lee… - Radiology, 2020 - pubs.rsna.org
… lung cancers on previous chestradiographs, we randomly … lung cancers on chestradiographs, and KHL, a chest radiologist with … learning-based automateddetection algorithm for major …
… Our results support several important observations regarding the use of CNNs for automated binary triage of chestradiographs, which to our knowledge has not been attempted at a …
EJ Hwang, S Park, KN Jin, J Im Kim, SY Choi… - JAMA network …, 2019 - jamanetwork.com
… Importance Interpretation of chestradiographs is a challenging task prone to errors, requiring expert readers. An automated system that can accurately classify chestradiographs may …
… imaging tests in medical practice, chestradiography requires timely reporting of potential … Automated, fast, and reliable detection of diseases based on chestradiography is a critical step …
… automated semantic labeling of medical images would be an efficient solution to this problem; our algorithm is well-suited for such rapid automated … of classifying chestradiographs into …
T Dyer, L Dillard, M Harrison, TN Morgan, R Tappouni… - Clinical radiology, 2021 - Elsevier
… chestradiograph is defined by the following criteria: a frontal image performed in inspiration showing a well-penetrated radiograph. … learning-based automateddetection algorithm for …
W Zhou, G Cheng, Z Zhang, L Zhu… - … Imaging in Medicine …, 2022 - ncbi.nlm.nih.gov
Background It is critical to have a deep learning-based system validated on an external dataset before it is used to assist clinical prognoses. The aim of this study was to assess the …
M Annarumma, SJ Withey, RJ Bakewell, E Pesce… - Radiology, 2019 - pubs.rsna.org
… Normal chestradiographs were detected by our AI system with a sensitivity of 71%, specificity of 95%, PPV of 73%, and NPV of 94%. The average reporting delay was reduced from …
S Arunmozhi, V Rajinikanth… - … , automation and …, 2021 - ieeexplore.ieee.org
… with chestradiographs (X-ray) due to its clinical significance. This work implements the deep-learning (DL) scheme to detect the pneumonia. The disease detection performance of the …