This should eventually be a comprehensive list of CXR datasets even if they are not in torchxrayvision

General pathology prediction

NIH ChestX-ray8 dataset, https://www.nih.gov/news-events/news-releases/nih-clinical-center-provides-one-largest-publicly-available-chest-x-ray-datasets-scientific-community https://arxiv.org/abs/1705.02315
RSNA Pneumonia Detection Challenge, https://www.rsna.org/en/education/ai-resources-and-training/ai-image-challenge/RSNA-Pneumonia-Detection-Challenge-2018 https://www.kaggle.com/c/rsna-pneumonia-detection-challenge
NIH Google, Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population-adjusted Evaluation https://pubs.rsna.org/doi/10.1148/radiol.2019191293
PadChest dataset, Hospital San Juan de Alicante – University of Alicante http://bimcv.cipf.es/bimcv-projects/padchest/
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. https://stanfordmlgroup.github.io/competitions/chexpert/
MIMIC-CXR: A large publicly available database of labeled chest radiographs. https://arxiv.org/abs/1901.07042 https://physionet.org/content/mimic-cxr-jpg/2.0.0/
OpenI https://openi.nlm.nih.gov/faq
COVID-19 image data collection https://github.com/ieee8023/covid-chestxray-dataset https://arxiv.org/abs/2003.11597
National Library of Medicine Tuberculosis Datasets https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4256233/
Pediatric bacterial and viral pneumonia chest X-rays, https://data.mendeley.com/datasets/rscbjbr9sj/3. Paper: https://www.cell.com/cell/fulltext/S0092-8674(18)30154-5.

Artifact detection

object-CXR, Automatic detection of foreign objects on chest X-rays, https://jfhealthcare.github.io/object-CXR/
ML-CDS 2020: Challenge, Detection of the presence of lines and tubes http://mcbr-cds.org/challenge/challenge-description.html https://arxiv.org/abs/1906.09336

v7labs COVID lung segmentations, https://github.com/v7labs/covid-19-xray-dataset