Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
SHR Neuro Krebs Kardio Lipid Stoffw Microb
Kreuzthaler, M; Pfeifer, B; Vera Ramos, JA; Kramer, D; Grogger, V; Bredenfeldt, S; Pedevilla, M; Krisper, P; Schulz, S.
EHR Text Categorization for Enhanced Patient-Based Document Navigation.
Stud Health Technol Inform. 2018; 248: 100-107.
PubMed
- Führende Autor*innen der Med Uni Graz
- Kreuzthaler Markus Eduard
- Co-Autor*innen der Med Uni Graz
- Krisper Peter
- Pfeifer Bastian
- Schulz Stefan
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- Abstract:
- Patients with multiple disorders usually have long diagnosis lists, constitute by ICD-10 codes together with individual free-text descriptions. These text snippets are produced by overwriting standardized ICD-Code topics by the physicians at the point of care. They provide highly compact expert descriptions within a 50-character long text field frequently not assigned to a specific ICD-10 code. The high redundancy of these lists would benefit from content-based categorization within different hospital-based application scenarios. This work demonstrates how to accurately group diagnosis lists via a combination of natural language processing and hierarchical clustering with an overall F-measure value of 0.87. In addition, it compresses the initial diagnosis list up to 89%. The manuscript discusses pitfall and challenges as well as the potential of a large-scale approach for tackling this problem.
- Find related publications in this database (using NLM MeSH Indexing)
- Electronic Health Records -
- Humans -
- International Classification of Diseases -
- Natural Language Processing -