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Showcase/RadQA: Radiology Report Question Answering Dataset
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RadQA: Radiology Report Question Answering Dataset

RadQA is an extractive QA dataset of physician questions answered by spans in MIMIC-III radiology reports, including unanswerable questions. This Potato config reproduces the span-marking and answerability task.

About this dataset

RadQA is a question answering dataset for radiology reports, built by Sarvesh Soni, Meghana Gudala, Atieh Pajouhi, and Kirk Roberts at the University of Texas Health Science Center at Houston. It was published at the LOUHI workshop (13th International Workshop on Health Text Mining and Information Analysis) in 2022.

The reports come from MIMIC-III, a public critical-care database. The authors selected 1,009 radiology reports from 100 patients and had physicians write 3,074 questions, annotated for a total of 6,148 question-answer evidence pairs. Splits are made at the patient level in an 8:1:1 ratio.

The task is extractive: each question is answered by marking the shortest span within the Findings and Impression sections of the report. Questions are written from the clinical referral section without seeing the answer context, which produces 1,754 unanswerable questions. This setup tests whether a model can both locate evidence and abstain when the report lacks an answer.

The Potato config below reproduces the RadQA annotation workflow: annotators read a clinical question and a radiology report, highlight answer or partial-answer spans, classify answerability, and record the answer type and extracted text.

Questions
3,074
QA evidence pairs
6,148
Unanswerable questions
1,754
Radiology reports
1,009
Patients
100
Source corpus
MIMIC-III
Q1: Rate your experience12345Q2: Primary use case?ResearchIndustryEducationQ3: Additional feedback

Configuration Fileconfig.yaml

This Potato config reproduces the annotation task. Save it as config.yaml and run potato start config.yaml to try it.

yaml
# RadQA: Radiology Report Question Answering
# Based on Soni et al., LREC 2022
# Paper: https://aclanthology.org/2022.lrec-1.672/
# Dataset: https://physionet.org/content/radqa/1.0.0/
#
# Task: Extractive question answering on clinical radiology reports
# Annotators read radiology reports and highlight answer spans that address
# clinical questions, classify answerability, and identify answer types.
#
# Annotation workflow:
# 1. Read the clinical question displayed above the report
# 2. Read the full radiology report carefully
# 3. Highlight the span(s) in the report that answer the question
# 4. Classify whether the question is answerable from the report
# 5. Identify the type of answer (finding, measurement, location, etc.)

annotation_task_name: "RadQA: Radiology Report Question Answering"
task_dir: "."

data_files:
  - sample-data.json
item_properties:
  id_key: "id"
  text_key: "report"

output_annotation_dir: "annotation_output/"
output_annotation_format: "json"

annotation_task_name: "RadQA Answer Extraction"

annotation_instructions: |
  You are performing extractive question answering on clinical radiology reports.

  **Instructions:**
  1. Read the **clinical question** displayed above the report text.
  2. Carefully read the entire **radiology report**.
  3. **Highlight** the text span(s) in the report that answer the question.
     - Use "answer" for spans that directly and fully answer the question.
     - Use "partial-answer" for spans that provide relevant but incomplete information.
  4. Classify whether the question is **answerable** from the report.
  5. Identify the **answer type** (what kind of clinical information the answer conveys).
  6. Copy the extracted answer text into the answer text field.

  **Important Notes:**
  - Select the minimal span that answers the question — do not include unnecessary context.
  - If the answer appears in multiple places, highlight the most informative occurrence.
  - Clinical abbreviations are acceptable in answer spans.
  - If the report does not contain information to answer the question, mark it as "unanswerable."

annotation_schemes:
  - annotation_type: span
    name: answer_span
    description: "Highlight the text span(s) in the report that answer the clinical question"
    labels:
      - "answer"
      - "partial-answer"
    label_colors:
      "answer": "#4caf50"
      "partial-answer": "#ff9800"
    tooltips:
      "answer": "Text that directly and fully answers the question"
      "partial-answer": "Text that provides relevant but incomplete information toward answering the question"
    allow_overlapping: false

  - annotation_type: radio
    name: answerability
    description: "Can the clinical question be answered from this radiology report?"
    labels:
      - name: "answerable"
        tooltip: "The report contains sufficient information to fully answer the question"
      - name: "unanswerable"
        tooltip: "The report does not contain information needed to answer the question"
      - name: "partially-answerable"
        tooltip: "The report contains some relevant information but not enough for a complete answer"
    keyboard_shortcuts:
      "answerable": "a"
      "unanswerable": "u"
      "partially-answerable": "p"

  - annotation_type: radio
    name: answer_type
    description: "What type of clinical information does the answer convey?"
    labels:
      - name: "finding"
        tooltip: "A clinical observation or abnormality (e.g., opacity, mass, effusion)"
      - name: "measurement"
        tooltip: "A quantitative value (e.g., size, volume, Hounsfield units)"
      - name: "location"
        tooltip: "An anatomical location or spatial relationship"
      - name: "comparison"
        tooltip: "A comparison with prior studies or temporal change"
      - name: "recommendation"
        tooltip: "A suggested follow-up action or further workup"
      - name: "diagnosis"
        tooltip: "A diagnostic impression or differential diagnosis"
    keyboard_shortcuts:
      "finding": "f"
      "measurement": "m"
      "location": "l"
      "comparison": "c"
      "recommendation": "r"
      "diagnosis": "d"

  - annotation_type: text
    name: answer_text
    description: "Copy the extracted answer text here (the text you highlighted as answering the question)"

html_layout: |
  <div style="margin-bottom: 12px; padding: 12px; background: #e3f2fd; border-radius: 6px; border-left: 4px solid #1565c0;">
    <strong>Report Type:</strong> {{report_type}}<br/>
    <strong style="font-size: 1.1em;">Question:</strong>
    <span style="font-size: 1.1em; color: #1565c0;">{{question}}</span>
  </div>
  <div style="padding: 12px; border: 1px solid #ddd; border-radius: 6px; line-height: 1.8; font-family: 'Courier New', monospace; background: #fafafa;">
    {{report}}
  </div>

allow_all_users: true
instances_per_annotator: 50
annotation_per_instance: 2
allow_skip: true
skip_reason_required: false

Sample Datasample-data.json

json
[
  {
    "id": "radqa_001",
    "report": "CHEST X-RAY, PA AND LATERAL. CLINICAL INDICATION: Shortness of breath. COMPARISON: Prior chest radiograph dated 3 days ago. FINDINGS: The heart size is mildly enlarged. There is a small left pleural effusion with associated left basilar atelectasis. The right lung is clear. No pneumothorax is identified. The mediastinal contours are unremarkable. Osseous structures are intact. IMPRESSION: 1. Small left pleural effusion with basilar atelectasis, new compared to prior study. 2. Mild cardiomegaly, stable.",
    "question": "Is there any pleural effusion present?",
    "report_type": "chest-xray"
  },
  {
    "id": "radqa_002",
    "report": "CT ABDOMEN AND PELVIS WITH CONTRAST. CLINICAL INDICATION: Abdominal pain, rule out appendicitis. COMPARISON: None. FINDINGS: The liver, spleen, pancreas, and adrenal glands appear normal. The kidneys enhance symmetrically without hydronephrosis or calculi. The appendix measures 11 mm in diameter with periappendiceal fat stranding and a 5 mm appendicolith at its base. There is mild free fluid in the pelvis. No bowel obstruction is identified. The abdominal aorta is normal in caliber. No pathologically enlarged lymph nodes are seen. IMPRESSION: Acute appendicitis with appendicolith. Recommend surgical consultation.",
    "question": "What is the diameter of the appendix?",
    "report_type": "ct-abdomen"
  }
]

// ... and 8 more items

Get This Design

View on GitHub

Clone or download from the repository

Quick start:

git clone https://github.com/davidjurgens/potato-showcase.git
cd potato-showcase/text/domain-specific/radqa-radiology-qa
potato start config.yaml

Dataset & paper

Soni et al., LREC 2022

Citation (BibTeX)

bibtex
@inproceedings{soni-etal-2022-radqa,
    title = "{R}ad{QA}: A Question Answering Dataset to Improve Comprehension of Radiology Reports",
    author = "Soni, Sarvesh and Gudala, Meghana and Pajouhi, Atieh and Roberts, Kirk",
    booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
    month = jun,
    year = "2022",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2022.lrec-1.672/",
    pages = "6250--6259"
}

Details

Annotation Types

radiospantext

Domain

Clinical NLPRadiologyQuestion Answering

Use Cases

Clinical Question AnsweringRadiology Report ComprehensionInformation Extraction

Tags

radiologyclinical-nlpquestion-answeringradqamedical

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