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Medical Informatics
Computing of umls concepts etiopathogenetic image
using graph metrics
P. A. Astanin, S. E. Rauzina, T. V. Zarubina Russian National Research Medical University named after N. I. Pirogov, Moscow, Russia
Abstract:
At present, the development of clinical decision support (CDS) tools
is a crucial task in medical informatics. A lot of different information searching
algorithms are used in CDS systems. A fundamental step in the design
of these algorithms is the creation of an etiopathogenetic image for the analysis
of unstructured medical texts. In this paper, we have conducted the literary
review and a comparative evaluation of analytical metrics used to compute
the etiopathogenetic image of concepts within the graph model of the Unified
Medical Language System (UMLS) metathesaurus. Subsequently, we developed
and validated our version of a graph metric suitable for the aforementioned task
implementation.
Key words and phrases:
hospital information system, information searching
algorithms, knowledge base, graph theory, UMLS.
Received: 30.03.2023 Accepted: 18.06.2023
Citation:
P. A. Astanin, S. E. Rauzina, T. V. Zarubina, “Computing of umls concepts etiopathogenetic image
using graph metrics”, Program Systems: Theory and Applications, 14:3 (2023), 59–94
Linking options:
https://www.mathnet.ru/eng/ps425 https://www.mathnet.ru/eng/ps/v14/i3/p59
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