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.
4 results indexed across 1 metric. Shaded row marks current SOTA; ties broken by submission date.
| # | Model | Org | Submitted | Paper / code | auroc |
|---|---|---|---|---|---|
| 01 | TorchXRayVisionOSS | Cohen Lab | Dec 2025 | github-readme | 85.80 |
| 02 | CheXNetOSS | Stanford ML Group | Dec 2025 | research-paper | 84.10 |
| 03 | DenseNet-121 (Chest X-ray)OSS | Research | Dec 2025 | research-paper | 82.60 |
| 04 | ResNet-50 (Chest X-ray)OSS | Research | Dec 2025 | research-paper | 80.40 |
Each row below marks a model that broke the previous record on auroc. Intermediate submissions are kept in the leaderboard above; only SOTA-setting entries are re-listed here.
Higher scores win. Each subsequent entry improved upon the previous best.
Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.