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<p>Developing natural language processing tools for clinical text requires annotated datasets, yet French oncology resources remain scarce. We present FRACCO (French Annotated Corpus for Clinical Oncology) an expert-annotated corpus of 1,301 synthetic French clinical cases, initially translated from the Spanish CANTEMIST corpus as part of the FRASIMED initiative. Each document is annotated with terms related to morphology, topography, and histologic differentiation, using the International Classification of Diseases for Oncology (ICD-O) as reference. An additional annotation layer captures composite expression-level normalisations that combine multiple ICD-O elements into unified clinical concepts. Annotation quality was ensured through expert review: 1,301 texts were manually annotated for entity spans by two domain experts. A total of 71,126 ICD-O normalisations were produced through a combination of automated matching and manual validation by a team of five annotators. The final dataset representing 399 unique morphology codes (from 2,290 different expressions), 273 topography codes (from 3,129 different expressions), and 3,041 unique composite expressions codes (from 10,740 different expressions). This dataset provides a reference standard for named entity recognition and concept normalisation in French oncology texts.</p>

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A gold-standard French-language annotated corpus of oncological entities with ICD-O normalisation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月30日

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  • Johann Pignat,
  • Milena Vucetic,
  • Christophe Gaudet-Blavignac,
  • Jamil Zaghir,
  • Amandine Stettler,
  • Fanny Amrein,
  • Jonatan Bonjour,
  • Jean-Philippe Goldman,
  • Olivier Michielin,
  • Christian Lovis,
  • Mina Bjelogrlic

摘要

Developing natural language processing tools for clinical text requires annotated datasets, yet French oncology resources remain scarce. We present FRACCO (French Annotated Corpus for Clinical Oncology) an expert-annotated corpus of 1,301 synthetic French clinical cases, initially translated from the Spanish CANTEMIST corpus as part of the FRASIMED initiative. Each document is annotated with terms related to morphology, topography, and histologic differentiation, using the International Classification of Diseases for Oncology (ICD-O) as reference. An additional annotation layer captures composite expression-level normalisations that combine multiple ICD-O elements into unified clinical concepts. Annotation quality was ensured through expert review: 1,301 texts were manually annotated for entity spans by two domain experts. A total of 71,126 ICD-O normalisations were produced through a combination of automated matching and manual validation by a team of five annotators. The final dataset representing 399 unique morphology codes (from 2,290 different expressions), 273 topography codes (from 3,129 different expressions), and 3,041 unique composite expressions codes (from 10,740 different expressions). This dataset provides a reference standard for named entity recognition and concept normalisation in French oncology texts.