CheXpedition: Investigating Generalization Challenges for Translation of Chest X-Ray Algorithms to the Clinical Setting

Investigating Generalization of Chest X-Ray Algorithms.

PDF) Multi-Domain Balanced Sampling Improves Out-of

Multi-task Learning for Chest X-ray Abnormality Classification on

PDF) A deep learning approach for the classification of TB from NIH CXR dataset

PediCXR: An open, large-scale chest radiograph dataset for interpretation of common thoracic diseases in children

Tuberculosis detection in chest radiograph using convolutional

CheXaid: deep learning assistance for physician diagnosis of tuberculosis using chest x-rays in patients with HIV

Recalibration of deep learning models for abnormality detection in

Example images of technical defects present in a radiograph. The

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

PDF) Automated Cardiothoracic Ratio Calculation and Cardiomegaly

Tuberculosis detection in chest radiograph using convolutional neural network architecture and explainable artificial intelligence

Chest x-ray automated triage: a semiologic approach designed for clinical implementation, exploiting different types of labels through a combination of four Deep Learning archi

Diagnostics, Free Full-Text

PDF] CheXternal: generalization of deep learning models for chest