Developing and Validating an Automatic Support System for Tumor Coding in Pathology Reports in Spanish
These results demonstrate the feasibility of implementing natural language processing tools in the routine of a cancer center to extract and code valuable information from pathology reports. Our recommender system allows reliable and transparent coding at the moment of consultation. This publication shares the annotated corpus in Spanish, annotation guidelines, and source code to reproduce our experiments.
Authors
- Jocelyn Dunstan (ORCID: https://orcid.org/0000-0001-6726-7242)
- Sergio Peñafiel (ORCID: https://orcid.org/0000-0002-0025-7805)
- Inti Paredes (ORCID: https://orcid.org/0009-0004-7712-9846)
- Pablo Báez (ORCID: https://orcid.org/0000-0003-2588-7747)
- Fabián Villena (ORCID: https://orcid.org/0000-0002-8759-466X)
- Matías Rojas (ORCID: https://orcid.org/0000-0003-0090-7748)
Institutions
- Universidad del Desarrollo (CL)
- Pontificia Universidad Católica de Chile (CL)
- Fundación Arturo López Pérez (CL)
- Metropolitan University of Technology (CL)
- Millennium Institute for Integrative Biology (CL)
- University of Chile (CL)
Publication Details
- Journal
- JCO Clinical Cancer Informatics
- Published
- 2025-02-01
- DOI
- https://doi.org/10.1200/cci.24.00124
- Citations
- 1
- Primary Topic
- Biomedical Text Mining and Ontologies
- Type
- article
- Field-Weighted Citation Impact
- 0.81