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

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.

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Publication Details

Journal
Scientific Data
Published
2026-06-30
DOI
https://doi.org/10.1038/s41597-026-07583-8
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Jean-Philippe Goldman, Johann Pignat, Mina Bjelogrlic, Christophe Gaudet-Blavignac et al.
Scientific Data
Biomedical Text Mining and Ontologies
article

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

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

Abstract

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.

Scientific Data
University of Geneva (CH), Hôpital Beau-Séjour (CH)
Fondation privée des Hôpitaux universitaires de Genève, National Centre of Competence in Research Evolving Language
Openalex Percentile: Top 12%
Biomedical Text Mining and Ontologies
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