Academic Journal
A domain-specific annotation framework and expert-annotated corpus for structured analysis of German HNSCC pathology reports.
| Τίτλος: | A domain-specific annotation framework and expert-annotated corpus for structured analysis of German HNSCC pathology reports. |
|---|---|
| Συγγραφείς: | Gubik S; Department of Oral and Maxillofacial Plastic Surgery - Head and Neck surgery, University Hospital of Würzburg, Pleicherwall 2, Würzburg, Germany. gubik_s@ukw.de., Seger F; Department of Oral and Maxillofacial Plastic Surgery - Head and Neck surgery, University Hospital of Würzburg, Pleicherwall 2, Würzburg, Germany., Vollmer A; Department of Oral and Maxillofacial Plastic Surgery - Head and Neck surgery, University Hospital of Würzburg, Pleicherwall 2, Würzburg, Germany., Hörner M; Department of Oral and Maxillofacial Plastic Surgery - Head and Neck surgery, University Hospital of Würzburg, Pleicherwall 2, Würzburg, Germany., Renner T; Department of Oral and Maxillofacial Plastic Surgery - Head and Neck surgery, University Hospital of Würzburg, Pleicherwall 2, Würzburg, Germany., Kohlhepp L; CAIDAS (Center of AI and Data Science), University Würzburg, Würzburg, Germany., Manthey M; Institute of Pathology, University of Würzburg, Würzburg, Germany., Müller-Richter U; Department of Oral and Maxillofacial Plastic Surgery - Head and Neck surgery, University Hospital of Würzburg, Pleicherwall 2, Würzburg, Germany., Kübler A; Department of Oral and Maxillofacial Plastic Surgery - Head and Neck surgery, University Hospital of Würzburg, Pleicherwall 2, Würzburg, Germany., Hackenberg S; Department of Otorhinolaryngology, Plastic, Aesthetic, and Reconstructive Head and Neck Surgery, University Hospital Würzburg, Würzburg, Germany., Hartmann S; Department of Oral and Maxillofacial Plastic Surgery - Head and Neck surgery, University Hospital of Würzburg, Pleicherwall 2, Würzburg, Germany. |
| Πηγή: | BMC research notes [BMC Res Notes] 2026 Sep 21; Vol. 19 (1). Date of Electronic Publication: 2026 Sep 21. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Biomed Central Country of Publication: England NLM ID: 101462768 Publication Model: Electronic Cited Medium: Internet ISSN: 1756-0500 (Electronic) Linking ISSN: 17560500 NLM ISO Abbreviation: BMC Res Notes Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: London : Biomed Central, 2008. |
| Ιατρικοί όροι (MeSH): | Head and Neck Neoplasms*/pathology , Squamous Cell Carcinoma of Head and Neck*/pathology , Data Mining*/methods , Natural Language Processing*, Humans ; Germany |
| Περίληψη: | Objective: To develop and empirically characterize a domain-specific, block-structured annotation schema and an expert-annotated reference corpus for German-language head and neck squamous cell carcinoma (HNSCC) pathology reports. Results Description: We retrieved 631 pathology reports from 145 patients treated at University Hospital Würzburg between January 2021 and March 2024 and split them at the patient level into training, validation, and evaluation subsets. Reports were manually annotated using a hierarchical, span-based schema supporting overlapping and nested annotations. The resulting corpus contains 45 unique labels organized into clinically meaningful blocks and an average of 37-39 annotations per report across subsets. Label frequencies and normalized category distributions were broadly comparable across the three subsets. Fine-grained labels were predominantly applied within their designated blocks, indicating adherence to the intended block structure. The corpus provides a domain-specific reference resource for developing and evaluating structured information-extraction approaches for German HNSCC pathology reports. (© 2026. The Author(s).) |
| Competing Interests: | Declarations. Ethics approval and consent to participate: This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the University of Würzburg (approval number: 20.02.2024/ag). Consent for publication: Not applicable. The manuscript does not contain any individual person’s data in any form (including individual details, images, or videos). Competing interests: The authors declare no competing interests. |
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| Contributed Indexing: | Keywords: Annotation schema; Clinical natural language processing; German medical texts; Head and neck cancer; Information extraction; Medical text mining; Pathology reports; TNM classification |
| Entry Date(s): | Date Created: 20260922 Date Completed: 20260922 Latest Revision: 20260924 |
| Update Code: | 20260924 |
| PubMed Central ID: | PMC13595725 |
| DOI: | 10.1186/s13104-026-08024-w |
| PMID: | 42768362 |
| Βάση Δεδομένων: | MEDLINE |
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