Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Schulz, S; Abdulnazar, A; Kreuzthaler, M.
Clustering Similar Diagnosis Terms.
Stud Health Technol Inform. 2023; 302: 837-838.
Doi: 10.3233/SHTI230284
PubMed
FullText
FullText_MUG
- Führende Autor*innen der Med Uni Graz
- Schulz Stefan
- Co-Autor*innen der Med Uni Graz
- Kreuzthaler Markus Eduard
- Kuppassery Abdulnazar Akhila Naz
- Altmetrics:
- Dimensions Citations:
- Plum Analytics:
- Scite (citation analytics):
- Abstract:
- A large clinical diagnosis list is explored with the goal to cluster syntactic variants. A string similarity heuristic is compared with a deep learning-based approach. Levenshtein distance (LD) applied to common words only (not tolerating deviations in acronyms and tokens with numerals), together with pair-wise substring expansions raised F1 to 13% above baseline (plain LD), with a maximum F1 of 0.71. In contrast, the model-based approach trained on a German medical language model did not perform better than the baseline, not exceeding an F1 value of 0.42.
- Find related publications in this database (using NLM MeSH Indexing)
- Natural Language Processing - administration & dosage
- Language - administration & dosage
- Electronic Health Records - administration & dosage
- Records - administration & dosage
- Cluster Analysis - administration & dosage