ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2019
Leveraging Non-lattice Subgraphs to Audit Hierarchical Relations in NCI Thesaurus.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Leveraging logical definitions and lexical features to detect missing IS-A relations in biomedical terminologies.Journal of biomedical semantics · 2024Article
- Identifying Missing IS-A Relations in SNOMED CT with Fine-Tuned Pre-trained Language Models and Non-lattice Subgraphs.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- A deep learning approach to identify missing is-a relations in SNOMED CT.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Identifying Missing IS-A Relations in Orphanet Rare Disease Ontology.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2022Article
- An evidence-based lexical pattern approach for quality assurance of Gene Ontology relations.Briefings in bioinformatics · 2022Article
- Automated Identification of Missing IS-A Relations in the Human Phenotype Ontology.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2022Article
- A Comparison of Exhaustive and Non-lattice-based Methods for Auditing Hierarchical Relations in Gene Ontology.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- Detecting missing IS-A relations in the NCI Thesaurus using an enhanced hybrid approach.BMC medical informatics and decision making · 2020Article
- A transformation-based method for auditing the IS-A hierarchy of biomedical terminologies in the Unified Medical Language System.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- A lexical-based approach for exhaustive detection of missing hierarchical IS-A relations in SNOMED CT.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020Article
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3 authors.
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Abstract
Auditing National Cancer Institute (NCI) thesaurus is essential to ensure that it provides accurate terminology for cancer-related clinical care as well as translational and basic research. We leverage a structural-lexical approach to identify missing hierarchical IS-A relations in NCI thesaurus based on non-lattice subgraphs and derived lexical attributes of concepts. For each concept in a non-lattice subgraph, we use two ways to derive the concept's lexical attributes: (1) inheriting lexical attributes from its ancestors within the subgraph; and (2) inheriting lexical attributes from all its ancestors. For a pair of concepts not having a hierarchical relation, if the lexical attributes of one concept is a subset of that of the other, we suggest there is a potential missing IS-A relation between the two concepts. Our approach identified 547 non-lattice subgraphs in the 19.01d release of NCI thesaurus which revealed a total of 1,022 unique potential missing IS-A relations. A random sample of 100 relations was evaluated by a domain expert. Among these relations, 90 can be obtained by the way of inheriting lexical attributes from ancestors within non-lattice subgraph, among which 76 were confirmed as valid (a precision of 84.44%); and 82 can be obtained by the way of inheriting all ancestors, among which 73 were confirmed as valid (a precision of 89.02%). The results show that our structural-lexical approach based on non-lattice subgraphs is effective for auditing NCI thesaurus.
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32308895PMC7153074What OpenQuestion holds
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