Disease Classification

1,112 resting-state fMRI datasets from 539 individuals with autism spectrum disorder (ASD) and 573 typically developing controls across 17 international sites. Multi-site neuroimaging data for autism classification and biomarker discovery.

224,316 chest radiographs from 65,240 patients with 14 pathology labels. Includes uncertainty labels and expert radiologist annotations for validation set. The gold standard for chest X-ray classification.

112,120 frontal-view chest X-ray images from 30,805 unique patients with 14 disease labels extracted using NLP from radiology reports. Foundational benchmark for chest X-ray AI.

377,110 chest X-ray images from 227,835 studies of 65,379 patients with free-text radiology reports. Largest publicly available chest X-ray dataset with paired image-text data.

Curated dataset of COVID-19 chest X-ray and CT images with clinical metadata. Critical resource during the pandemic for developing AI diagnostic tools.

1,114 datasets from 521 individuals with autism spectrum disorder (ASD) and 593 typically developing controls across 19 sites. Second large-scale release complementing ABIDE I with additional multi-site neuroimaging data.

30,000 frontal chest radiographs with bounding boxes for pneumonia detection. From 2018 RSNA Kaggle competition. Tests both classification and localization.

18,000 chest X-ray scans with radiologist annotations for 22 local labels and 6 global labels. Each image annotated by 3 radiologists with bounding box localization.

160,868 images from 67,625 patients with 174 radiographic findings, 19 diagnoses, and 104 anatomic locations. Multi-label classification with hierarchical taxonomy.