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CheXpert

224,316 chest X-rays from Stanford with automated + expert labels for 14 observations.

LQS 79 · gold ⚠ Research-only 224K X-ray images 440 GB JPG · CSV Released 2019
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Source: stanfordmlgroup.github.io · maintained by Stanford ML Group
224K
X-ray images
440 GB
Size on disk
79
LQS · gold
2019
First released

About this dataset

CheXpert is Stanford ML Group's chest radiograph dataset. 224,316 chest X-rays of 65,240 patients with expert-labeled test set and rule-based training labels for 14 observations. The validation set has 8 expert radiologist labels per image for robust evaluation.

Maintainer
Formats
JPG · CSV

LabelSets Quality Score

LQS is our 7-dimension quality score, computed from the dataset's published statistics. See methodology →

79
out of 100
gold tier

Solid dataset with some trade-offs

Composite score computed from the 7 dimensions below: completeness, uniqueness, validation health, size adequacy, format compliance, label density, and class balance.

Completeness 85
No public completeness metric; using prior for 'automated' datasets.
Uniqueness 93
Exact-hash deduplication documented by maintainer.
Validation 68
Labels auto-extracted from free-text reports — typical ~90% accuracy.
Size adequacy 93
224,316 images — exceeds 20,000 adequacy target for Medical Imaging.
Format compliance 95
Industry-standard format — drop-in compatible with mainstream tooling.
Label density 52
Average 1.0 labels per item (sparse).
Class balance 58
Long-tail distribution — dominant classes overrepresented.

What it's used for

Common tasks and benchmarks where CheXpert is the default or competitive choice.

Sample statistics

What's actually in the dataset — from the maintainer's published stats.

224,316 images from 65,240 patients. 14 observations per image. Validation set has multi-radiologist ground truth (8 experts).

License

CheXpert is distributed under Stanford Research Use License. This is a third-party public dataset; LabelSets indexes and scores it but does not host or redistribute the data. Always verify current license terms with the maintainer before commercial use.

Heads up: this dataset's license restricts commercial use. If you need medical imaging data for production, check LabelSets' paid datasets below — every listing has an explicit commercial license.

Need commercial-licensed Medical Imaging data?

LabelSets sellers offer paid medical imaging datasets with what public datasets often can't give you:

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Similar public datasets

Other entries in the Medical Imaging catalog.

Frequently Asked Questions

CheXpert is distributed under Stanford Research Use License, which restricts commercial use. For a commercially-licensed alternative in medical imaging, see LabelSets' paid datasets.
CheXpert contains 224,316 X-ray images. 224,316 images from 65,240 patients. 14 observations per image. Validation set has multi-radiologist ground truth (8 experts).
CheXpert is maintained by Stanford ML Group and is available at https://stanfordmlgroup.github.io/competitions/chexpert/. LabelSets indexes and scores this dataset for discoverability but does not redistribute it.
LQS is a 7-dimension quality score (completeness, uniqueness, validation, size adequacy, format compliance, label density, class balance) computed from the dataset's published statistics. Composite scores map to tiers: platinum (≥90), gold (≥75), silver (≥60), bronze (<60). Read the full methodology.