Radiology Report Text Extraction

This dataset contains synthetic radiology report texts with structured fields for patient demographics, imaging modality, body part examined, and detailed report content. It includes optional annotations for clinical entities, report classifications, and summaries, making it ideal for developing and benchmarking NLP models in medical imaging. The dataset supports entity recognition, classification, and summarization tasks, facilitating research in healthcare AI and clinical decision support.

  • opened 6 times
  • last updated 22 Jul 2025
  • by GoMask
The brief that made it

Training and evaluating NLP models for clinical entity recognition in radiology reports

Sample rows

preview · 8 of 200 rows · all 12 columns
report_idstringreport_classificationstringageintegerbody_part_examinedstringpatient_idstringstudy_datedatemodalitystringsexstringreport_textstringimpression_textstringentities_annotatedstringsummary_textstring
RPT-00001Normal27ChestPAT-00012022-02-17X-rayFemaleFrontal chest X-ray demonstrates clear lungs, no focal consolidation, pleural effusion, or pneumothorax. Cardiac silhouette within normal limits.Normal chest X-ray. No acute findings.{"entities": [{"text": "clear lungs", "type": "finding", "start": 29, "end": 40}]}No abnormality detected in chest X-ray.
RPT-00002Abnormal45AbdomenPAT-00022019-12-03CTMaleCT scan of the abdomen shows mild hepatic steatosis, no evidence of hepatomegaly, splenomegaly or mass lesion. No ascites seen.Mild fatty liver. Otherwise unremarkable study.{"entities": [{"text": "hepatic steatosis", "type": "pathology", "start": 32, "end": 49}]}Fatty liver noted; all other findings normal.
RPT-00003Abnormal74BrainPAT-00032021-05-22MRIFemaleMRI brain reveals no acute infarct or hemorrhage. Mild periventricular white matter changes consistent with chronic microvascular ischemia.Chronic microvascular changes. No acute event.{"entities": [{"text": "chronic microvascular ischemia", "type": "pathology", "start": 88, "end": 118}]}Chronic small vessel changes, no acute stroke.
RPT-00004Follow-up Recommended53ThyroidPAT-00042024-01-16UltrasoundFemaleUltrasound of the thyroid demonstrates a 1.2 cm hypoechoic nodule in the right lobe. No suspicious lymphadenopathy is identified.Right thyroid nodule, benign features.{"entities": [{"text": "1.2 cm hypoechoic nodule", "type": "finding", "start": 40, "end": 64}]}Right thyroid nodule, suggest follow-up.
RPT-00005Normal52Breast rightPAT-00052022-08-05MammographyFemaleScreening mammogram of the right breast shows dense glandular tissue with no discrete mass, microcalcifications, or architectural distortion.Dense tissue, no suspicious findings.{"entities": [{"text": "dense glandular tissue", "type": "finding", "start": 37, "end": 59}]}Normal right breast mammogram.
RPT-00006Abnormal19HandPAT-00062023-05-09X-rayMaleX-ray of the left hand shows a non-displaced fracture of the fifth metacarpal shaft with minimal soft tissue swelling.Non-displaced fifth metacarpal fracture.{"entities": [{"text": "non-displaced fracture", "type": "finding", "start": 34, "end": 56}]}Left hand fracture noted.
RPT-00007Critical68Whole bodyPAT-00072021-07-13PETMaleWhole body PET scan demonstrates increased uptake in mediastinal lymph nodes, concerning for metastatic disease.Suspicious for mediastinal metastases.{"entities": [{"text": "increased uptake in mediastinal lymph nodes", "type": "finding", "start": 35, "end": 76}]}Possible mediastinal metastases detected.
RPT-00008Abnormal25SinusesPAT-00082020-06-24CTFemaleCT of the paranasal sinuses reveals mucosal thickening in the left maxillary sinus and mild nasal septal deviation.Mild sinus mucosal thickening.{"entities": [{"text": "mucosal thickening", "type": "finding", "start": 41, "end": 59}]}Mild left maxillary sinusitis.

What the 200 rows show

from the 200-row sample

Critical (report classification) stands out: mean age is 71.7, against 44.3 for the rest.

  • 49.5median age
  • 4sexes
  • 7modalities
Mean age by report_classification200 rows
0408034.1Normal64 rows48.8Abnorm…72 rows71.7Critic…28 rows51.9Follow…22 rows55.9Other14 rows
age200 rows, in bands of 10
02040710232931323723805090age →

Median 49.5, from 0 to 85.

body_part_examined200 rows · top 10 of 28 values
  1. Chest38
  2. Abdomen16
  3. Brain14
  4. Liver14
  5. Thyroid12
  6. Spine11
  7. Sinuses10
  8. Head10
  9. Hand8
  10. Foot8
12 columns by typefrom the column list below
  • string 10
  • integer 1
  • date 1

Columns

12 columns in three groups
blueprint · 12 columns
columntypedescriptionexample
Text 10 columns
report_idstringUnique identifier for each radiology reportuniqueRPT-00001
patient_idstringAnonymized unique identifier for the patient associated with the reportPAT-0001
modalitystringType of imaging modality used (e.g., X-ray, CT, MRI, Ultrasound)7 valuesX-ray
body_part_examinedstringBody part or region examined in the radiology studyChest
report_textstringFull text of the radiology report as written by the radiologistFrontal chest X-ray demon…
impression_textstringSummary or impression section of the radiology report, if availableoptionalNormal CT of head.
entities_annotatedstringJSON-encoded list of recognized clinical entities (e.g., findings, anatomical sites, pathologies) with their positions/types for NLP tasksoptional{"entities": [{"text": "c…
report_classificationstringLabel or category assigned to the report for classification tasks (e.g., Normal, Abnormal, Critical, Follow-up Recommended)Normal · Abnormal · Critical · Follow-up Recommended · Other · optionalNormal
summary_textstringMachine-generated or human-written summary of the report for summarization tasksoptionalNormal chest X-ray.
sexstringSex of the patientMale · Female · Other · Unknown · optionalFemale
Numbers 1 column
ageintegerAge of the patient at the time of the study (in years)0 to 120 · optional27
Dates and times 1 column
study_datedateDate when the radiology study was performed2022-02-17

Use it for

  • median age49.5200 rowsmean age by report cl…34.1Norm…48.8Abno…71.7Crit…51.9Foll…

    A healthcare dashboard

    Age by report_classification and a breakdown of body_part_examined. Excel, Power BI or Tableau.

  • Why do the 28 Critical rows have a mean age of 71.7?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable reports with patient_id, study_date and modality to fill a screen in front of a buyer.

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This dataset200 rows12 columns
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blueprint · radiology-report-text-extraction

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 12 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Reports generated from common imaging modalities: CT, MRI, X-ray
  • Each report contains anonymized patient demographics
  • Findings and impressions clearly separated
  • Medical abbreviations and synonyms included
Rows
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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
radiology-report-text-extraction

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