Efficient Clinical Information Extraction from Breast Radiology Reports in French.
Breast cancer
NLP
Radiology report
text classification
Journal
Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582
Informations de publication
Date de publication:
22 Aug 2024
22 Aug 2024
Historique:
medline:
23
8
2024
pubmed:
23
8
2024
entrez:
23
8
2024
Statut:
ppublish
Résumé
Radiology reports contain crucial patient information, in addition to images, that can be automatically extracted for secondary uses such as clinical support and research for diagnosis. We tested several classifiers to classify 1,218 breast MRI reports in French from two Swiss clinical centers. Logistic regression performed better for both internal (accuracy > 0.95 and macro-F1 > 0.86) and external data (accuracy > 0.81 and macro-F1 > 0.41). Automating this task will facilitate efficient extraction of targeted clinical parameters and provide a good basis for future annotation processes through automatic pre-annotation.
Identifiants
pubmed: 39176562
pii: SHTI240776
doi: 10.3233/SHTI240776
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM