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

Investigating Generalization of Chest X-Ray Algorithms.

Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning

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

Chest x-ray automated triage: a semiologic approach designed for

Frontiers Deployment and validation of an AI system for

Tuberculosis detection in chest radiograph using convolutional neural network architecture and explainable artificial intelligence. - Abstract - Europe PMC

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

Frontiers Deployment and validation of an AI system for detecting abnormal chest radiographs in clinical settings

PDF] CheXtransfer: performance and parameter efficiency of

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

PDF] CheXphoto: 10, 000+ Smartphone Photos and Synthetic Photographic Transformations of Chest X-rays for Benchmarking Deep Learning Robustness

Jeremy IRVIN, Stanford University, CA, SU

Endotracheal Tube Detection and Segmentation in Chest Radiographs

Diagnostics, Free Full-Text

Artificial intelligence in radiology - ScienceDirect

PDF] CheXphotogenic: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays