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Codesota · Benchmark · NIH ChestX-ray14Home/Leaderboards/NIH ChestX-ray14
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NIH ChestX-ray14.

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.

Paper Leaderboard
§ 01 · Leaderboard

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auroc

Auroc is the reported evaluation metric for NIH ChestX-ray14. Codesota tracks published model scores on this metric so readers can compare state-of-the-art results across sources and model families.

Higher is better

Trust tiers for aurocverifiedpapervendorcommunityunverified
RankModelTrustScoreYearLinksEdit
01TorchXRayVision
Multi-dataset pre-training improves over single-dataset.
unverified85.82025Source ↗Edit result
02chexnet
Original CheXNet on ChestX-ray14. Exceeded radiologist performance on pneumonia (0.768 vs 0.633).
paper84.12025Source ↗Edit result
03DenseNet-121 (Chest X-ray)
Original NIH baseline model.
paper82.62025Source ↗Edit result
04densenet-121-cxr
Original NIH baseline model.
paper82.62025Source ↗Edit result
05ResNet-50 (Chest X-ray)
ResNet-50 baseline.
paper80.42025Source ↗Edit result
06resnet-50-cxr
ResNet-50 baseline.
paper80.42025Source ↗Edit result
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