| | --- |
| | license: mit |
| | task_categories: |
| | - question-answering |
| | language: |
| | - fr |
| | tags: |
| | - medical |
| | - biology |
| | size_categories: |
| | - 10K<n<100K |
| | --- |
| | |
| | # MedInjection-FR — Native Subset 🇫🇷 |
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| | ## Summary |
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| | The **Native** component of **MedInjection-FR** comprises **French biomedical instructions and question–answer pairs** natively written in French. |
| | It forms the core of the dataset and reflects **authentic medical reasoning and linguistic formulations**, sourced from curated corpora and educational materials. |
| | This subset serves as the **high-quality reference supervision** for instruction tuning of large language models (LLMs) in French biomedical contexts. |
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| | ## Motivation |
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| | Instruction tuning has become essential for adapting LLMs to domain-specific prompts. Yet, in medicine, **native French supervision remains scarce**. |
| | The Native subset bridges this gap, providing instruction–response data derived directly from **French medical exams, textbooks, and clinical resources**, preserving authentic phrasing, domain structure, and context. |
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| | ## Composition |
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| | The native component combines curated datasets and web-scraped French medical resources to reflect authentic domain knowledge. It integrates the following resources: |
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| | - **[S-Editions](https://s-editions.fr/)** |
| | 526 question–answer pairs from a French educational platform for medical students. |
| |
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| | - **[MediQAl](https://github.com/abazoge/MediQAl)**: |
| | 32 603 items from national medical examinations covering 41 medical specialties. |
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| | - **[FrenchMedMCQA](https://arxiv.org/abs/2304.04280)**: |
| | 3 105 pharmacy-focused multiple-choice questions. |
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| | - **[mlabonne/medical-cases-fr](https://huggingface.co/datasets/mlabonne/medical-cases-fr)** and **[mlabonne/medical-mcqa-fr](https://huggingface.co/datasets/mlabonne/medical-mcqa-fr)**: |
| | 12 194 examples originating from French medical exam databases. |
| |
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| | - **[FrBMedQA](https://www.researchgate.net/publication/365908538_FrBMedQA_the_first_French_biomedical_question_answering_dataset)**: |
| | 19 836 questions derived from French biomedical Wikipedia articles spanning eight UMLS semantic groups (chemicals and drugs, anatomy, physiology, disorders, phenomena, procedures, genes and molecular sequences, and devices). |
| | Originally closed-form, these questions were reformulated into multiple-choice format using *[GPT-4o-mini](https://openai.com/research/gpt-4o)* for standardization. |
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| | - **[Biomedical Translation Corpora (WMT)](https://github.com/biomedical-translation-corpora/corpora)**: |
| | Bilingual biomedical translation data from the WMT challenge repositories were reformulated into instruction–response pairs. |
| | Each instruction requests the **French translation** of an English biomedical passage, reframing translation as an instruction-following task aligned with the native portion. |
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| | ## Use |
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| | Used to fine-tune biomedical LLMs for: |
| | - Question answering and clinical reasoning |
| | - Instruction-following in French |
| | - Evaluating cross-domain instruction generalization |
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