MedQAData-FR: French Medical Question-Answering Dataset

A French-focused medical question-answering dataset derived from MedQAData-v2. It contains patient narratives, reformulated questions, and doctor answers annotated with urgency and medical specialty. The dataset was created by Williamsanderson and was last updated on the Hugging Face platform in April 2026.

Use Cases

• Training medical question-answering models based on patient narratives and doctor answers.
• Developing urgency classification systems based on the annotated urgency levels.
• Analyzing medical language and terminology within a specific specialty based on the specialty field.
• Extracting and studying medical entities like symptoms and diseases based on the entities dictionary.

Strengths

• Includes structured annotations for urgency (low/medium/high/critical) and medical specialty.
• Contains a dictionary of extracted entities including age, medication, symptoms, and diseases.
• Provides both a full patient narrative (context_question) and a concise reformulated question.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

Derived from MedQAData-v2.

Freshness

Last updated 2026-04-29 23:23:22; freshness should be verified.

Geography

France or French-speaking regions.