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Codesota · Benchmark · CheXpertHome/Leaderboards/CheXpert
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CheXpert.

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.

Paper Leaderboard
§ 01 · Leaderboard

Results by metric.

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auroc

Auroc is the reported evaluation metric for CheXpert. 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
01chexpert-auc-maximizer
Mean AUC across 5 competition pathologies. Competition-winning ensemble.
paper932025Source ↗Edit result
02CheXpert AUC Maximizer
Mean AUC across 5 competition pathologies. Competition-winning ensemble.
unverified932025Source ↗Edit result
03BioViL
Microsoft's biomedical vision-language model.
unverified89.12025Source ↗Edit result
04chexzero
Zero-shot performance without task-specific training. Expert-level on multiple pathologies.
paper88.62025Source ↗Edit result
05GLoRIA
Global-Local Representations. Zero-shot evaluation.
paper88.22025Source ↗Edit result
06MedCLIP
Decoupled contrastive learning. Zero-shot transfer.
paper87.82025Source ↗Edit result
07TorchXRayVision
Pre-trained on multiple datasets. Strong transfer learning baseline.
unverified87.42025Source ↗Edit result
08DenseNet-121 (Chest X-ray)
Baseline DenseNet-121. Trained on CheXpert training set.
paper86.52025Source ↗Edit result
09densenet-121-cxr
Baseline DenseNet-121. Trained on CheXpert training set.
paper86.52025Source ↗Edit result
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