ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium
Combining rules, background knowledge and change patterns to maintain semantic annotations.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Models and Approaches for Comprehension of Dysarthric Speech Using Natural Language Processing: Systematic Review.JMIR rehabilitation and assistive technologies · 2023Review
- Analysis and implementation of the DynDiff tool when comparing versions of ontology.Journal of biomedical semantics · 2023Article
- Amplifying Domain Expertise in Clinical Data Pipelines.JMIR medical informatics · 2020Article
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Authors and funding
4 authors.
Funding
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Abstract
Knowledge Organization Systems (KOS) play a key role in enriching biomedical information in order to make it machine-understandable and shareable. This is done by annotating medical documents, or more specifically, associating concept labels from KOS with pieces of digital information, e.g., images or texts. However, the dynamic nature of KOS may impact the annotations, thus creating a mismatch between the evolved concept and the associated information. To solve this problem, methods to maintain the quality of the annotations are required. In this paper, we define a framework based on rules, background knowledge and change patterns to drive the annotation adaption process. We evaluate experimentally the proposed approach in realistic cases-studies and demonstrate the overall performance of our approach in different KOS considering the precision, recall, F1-score and AUC value of the system.
Indexed as
Identifiers
29854115PMC5977713What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.