Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Abdulnazar, A; Schulz, S; Kreuzthaler, M.
Smoking Status Normalization with Cross-Encoders and SNOMED CT.
Stud Health Technol Inform. 2025; 327:818-822
Doi: 10.3233/SHTI250473
PubMed
FullText
FullText_MUG
- Führende Autor*innen der Med Uni Graz
- Kuppassery Abdulnazar Akhila Naz
- Co-Autor*innen der Med Uni Graz
- Kreuzthaler Markus Eduard
- Schulz Stefan
- Altmetrics:
- Dimensions Citations:
- Plum Analytics:
- Scite (citation analytics):
- Abstract:
- Accurately documenting smoking status is essential for clinical decision-making and patient care. However, smoking status information is often only available in clinical narratives. Mapping smoking-related terms to standardized terminologies such as SNOMED CT enhances interoperability and consistency across healthcare systems. We employed a bi-encoder and cross-encoder re-ranking model to normalize possible mentions of smoking status in clinical narratives by assigning SNOMED CT codes, achieving standardized representations. Our investigation achieved 85% accuracy for Recall@1, successfully mapping smoking-related narrative expressions to SNOMED CT definitions in German.
- Find related publications in this database (using NLM MeSH Indexing)
- Systematized Nomenclature of Medicine - administration & dosage
- Humans - administration & dosage
- Smoking - administration & dosage
- Electronic Health Records - standards
- Natural Language Processing - administration & dosage
- Germany - administration & dosage