Pith Number

pith:27VZKU34

pith:2019:27VZKU34OVNW73436WUSTFXXCD

not attested not anchored not stored refs resolved

MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs

Alistair E. W. Johnson, Chih-ying Deng, Matthew P. Lungren, Nathaniel R. Greenbaum, Roger G. Mark, Seth J. Berkowitz, Steven Horng, Tom J. Pollard, Yifan Peng, Zhiyong Lu

A large dataset of 377,110 labeled chest x-rays is now publicly available for medical computer vision research.

arxiv:1901.07042 v5 · 2019-01-21 · cs.CV · cs.LG · eess.IV

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{27VZKU34OVNW73436WUSTFXXCD}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

MIMIC-CXR-JPG v2.0.0 is a large dataset of 377,110 chest x-rays associated with 227,827 imaging studies... Images are provided with 14 labels derived from two natural language processing tools applied to the corresponding free-text radiology reports.

C2weakest assumption

The 14 labels produced by the two NLP tools accurately capture the clinical content of the radiology reports and correspond to verifiable findings in the images.

C3one line summary

MIMIC-CXR-JPG provides 377,110 labeled chest X-rays derived from MIMIC-CXR with NLP-generated labels and standard splits for medical imaging AI development.

References

20 extracted · 20 resolved · 0 Pith anchors

[1] The US radiologist workforce: an analysis of temporal and geographic variation by using large national datasets 2015

[2] A county-level analysis of the US radiologist workforce: physician supply and subspecialty characteristics 2018

[3] Radiologist shortage leaves patient care at risk, warns royal college 2017

[4] Improving Patient Safety: Avoiding Unread Imaging Exams in the National V A Enterprise Electronic Health Record 2017

[5] Imaging in the land of 1000 hills: Rwanda radiology country report 2015

Formal links

1 machine-checked theorem link

Cited by

29 papers in Pith

Boosting the rule-out accuracy of deep disease detection using class weight modifiers

M4CXR: Exploring Multi-task Potentials of Multi-modal Large Language Models for Chest X-ray Interpretation

Image-to-Text for Medical Reports Using Adaptive Co-Attention and Triple-LSTM Module

RA-RRG: Multimodal Retrieval-Augmented Radiology Report Generation with Key Phrase Extraction

MI-CXR: A Benchmark for Longitudinal Reasoning over Multi-Interval Chest X-rays

Receipt and verification

First computed	2026-05-17T23:38:15.154275Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d7eb95537c755b6fef9bf5a92996f710f74d777ac296a0b8b300363a1b3f5af9

Aliases

arxiv: 1901.07042 · arxiv_version: 1901.07042v5 · doi: 10.48550/arxiv.1901.07042 · pith_short_12: 27VZKU34OVNW · pith_short_16: 27VZKU34OVNW7343 · pith_short_8: 27VZKU34

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/27VZKU34OVNW73436WUSTFXXCD \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: d7eb95537c755b6fef9bf5a92996f710f74d777ac296a0b8b300363a1b3f5af9

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "639dce0f9864968c4a8b6512ba0a98f110bd85dfc65d509a73d3b861224262a9",
    "cross_cats_sorted": [
      "cs.LG",
      "eess.IV"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2019-01-21T19:01:00Z",
    "title_canon_sha256": "24cfb386d9a7373fa8fa9d036b1aa0ee88e836ad71c982b120129e6ecd275082"
  },
  "schema_version": "1.0",
  "source": {
    "id": "1901.07042",
    "kind": "arxiv",
    "version": 5
  }
}