Pre-coding skin cancer from free-text pathology reports using noise-robust neural networks
We piloted our method in the Vaud Cancer Registry, Switzerland. It was able to identify and pre-code skin cancer cases efficiently and find correct key terms in reports. Medical coders found pre-coding useful and time saving. Integration of the method in the registry document workflow and its extension to other cancer types are intended.
Authors
- Gautier Défossez (ORCID: https://orcid.org/0000-0002-7615-954X)
- Tapio Niemi (ORCID: https://orcid.org/0000-0003-0184-8946)
- Simon Germann
- Jean‐Luc Bulliard (ORCID: https://orcid.org/0000-0001-9750-2709)
Institutions
- Centre universitaire de médecine générale et santé publique, Lausanne (CH)
- University of Lausanne (CH)
Publication Details
- Journal
- Journal of Biomedical Informatics
- Published
- 2025-10-25
- DOI
- https://doi.org/10.1016/j.jbi.2025.104943
- Primary Topic
- Nonmelanoma Skin Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00