… radiographs: a novel approach achieving expert radiologist-level performance using a deep convolutional neural network trained on digital reconstructed radiographs …

EJM Barbosa Jr, WB Gefter, FC Ghesu, S Liu… - Investigative …, 2021 - journals.lww.com
… To avoid overfitting, we used a validation dataset containing 182 DRRs to select the
model with early-stopping. The processing time of the system to compute POa, including …

Estimating the accuracy of dual energy chest radiography for coronary calcium detection with lateral or anteroposterior orientations

SS Hsieh, MJ Budoff - Medical physics, 2022 - Wiley Online Library
… The fraction of CT CAC scores in the validation set of 0, 1–99… Two readers read the validation
set in a blinded, randomized … could be excluded in clinical deployment of DE CXR with …

Automated abnormality classification of chest radiographs using deep convolutional neural networks

YX Tang, YB Tang, Y Peng, K Yan, M Bagheri… - NPJ digital …, 2020 - nature.com
… 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 …

Deep learning to estimate lung disease mortality from chest radiographs

J Weiss, VK Raghu, D Bontempi, DC Christiani… - Nature …, 2023 - nature.com
… In this context, CXR-Lung-Risk could be deployed to automatically notify the treating … This
cloud-based instance facilitates future validation studies and allows users with minimal coding …

Recalibration of deep learning models for abnormality detection in smartphone-captured chest radiograph

PC Kuo, CC Tsai, DM López, A Karargyris… - NPJ digital …, 2021 - nature.com
… Again, we reached similar results as those in internal or external validation. The recalibrated
model (… and the recalibrated model has potential to be deployed to the real clinical works. …

Automated detection of moderate and large pneumothorax on frontal chest X-rays using deep convolutional neural networks: A retrospective study

AG Taylor, C Mielke, J Mongan - PLoS medicine, 2018 - journals.plos.org
… previously developed chest radiograph orientation model [14… model performance on the
validation set every 10 training … into the development and deployment of truly useful artificial …

Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration

S Candemir, S Jaeger, K Palaniappan… - IEEE transactions on …, 2013 - ieeexplore.ieee.org
… ing a digital chest x-ray (CXR) screening system for deployment in resource constrained …
approach compared to other state-of-the-art methods using the validated Japanese Society …

Model development for pneumonia detection from chest radiograph using transfer learning

OA Fagbuagun, O Nwankwo… - TELKOMNIKA …, 2022 - telkomnika.uad.ac.id
… have aroused research interests and has been deployed for the diagnosis of lung nodule
[29… The validation set were 16 images while the test set were 624 images. Labels were given to …

Deep learning to quantify pulmonary edema in chest radiographs

S Horng, R Liao, X Wang, S Dalal, P Golland… - Radiology: Artificial …, 2021 - pubs.rsna.org
… To validate our label extraction in radiology reports, we randomly selected 200 labeled …
clearly critical before such a model could be deployed in clinical practice. Importantly, however, …

[HTML][HTML] A prospective observational study to investigate performance of a chest X-ray artificial intelligence diagnostic support tool across 12 US hospitals

J Sun, L Peng, T Li, D Adila, Z Zaiman, GB Melton… - ArXiv, 2021 - ncbi.nlm.nih.gov
… including: the lack of external validation 6 , lack of equity analysis by … the environment where
the model will ultimately be deployed. … developed and temporally validated by August, 2020. …