ArticleJournal of biomedical semantics2016
Interoperability between phenotypes in research and healthcare terminologies--Investigating partial mappings between HPO and SNOMED CT.
Article in Journal of biomedical semantics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed, 44 citations in OpenAlex.
- Application of the International Classification of Health Interventions for coding interventions in adults with sensorineural hearing loss.JAMIA open · 2025Article
- The Human Phenotype Ontology in 2024: phenotypes around the world.Nucleic acids research · 2024Article
- Ontologizing health systems data at scale: making translational discovery a reality.NPJ digital medicine · 2023Article
- Automated approach for quality assessment of RDF resources.BMC medical informatics and decision making · 2023Article
- Linking rare and common disease vocabularies by mapping between the human phenotype ontology and phecodes.JAMIA open · 2023Article
- Standardized Description of the Feature Extraction Process to Transform Raw Data Into Meaningful Information for Enhancing Data Reuse: Consensus Study.JMIR medical informatics · 2022Article
- Common genetic variation associated with Mendelian disease severity revealed through cryptic phenotype analysis.Nature communications · 2022Article
- Rare Disease Registries Are Key to Evidence-Based Personalized Medicine: Highlighting the European Experience.Frontiers in endocrinology · 2022Review
- A State-of-the Art Review of SNOMED CT Terminology Binding and Recommendations for Practice and Research.Methods of information in medicine · 2021Article
- [Application of the artificial intelligence-rapid whole-genome sequencing diagnostic system in the neonatal/pediatric intensive care unit].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2021Article
- The Human Phenotype Ontology in 2021.Nucleic acids research · 2021Article
- Assessing the enrichment of dietary supplement coverage in the Unified Medical Language System.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Clinical data quality: a data life cycle perspective.Biostatistics & epidemiology · 2020Article
- Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation.Science translational medicine · 2019Article
- Integrating an Ontology of Radiology Differential Diagnosis with ICD-10-CM, RadLex, and SNOMED CT.Journal of digital imaging · 2019Article
- Integrating ontologies of human diseases, phenotypes, and radiological diagnosis.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Ontological and Non-Ontological Resources for Associating Medical Dictionary for Regulatory Activities Terms to SNOMED Clinical Terms With Semantic Properties.Frontiers in pharmacology · 2019Article
- Deep Phenotyping on Electronic Health Records Facilitates Genetic Diagnosis by Clinical Exomes.American journal of human genetics · 2018Article
- The LOINC RSNA radiology playbook - a unified terminology for radiology procedures.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Improving the interoperability of biomedical ontologies with compound alignments.Journal of biomedical semantics · 2018Article
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2 authors at 1 institution in 1 country.
Funding
Abstract
backgroundIdentifying partial mappings between two terminologies is of special importance when one terminology is finer-grained than the other, as is the case for the Human Phenotype Ontology (HPO), mainly used for research purposes, and SNOMED CT, mainly used in healthcare.
objectivesTo investigate and contrast lexical and logical approaches to deriving partial mappings between HPO and SNOMED CT.
methods1) Lexical approach-We identify modifiers in HPO terms and attempt to map demodified terms to SNOMED CT through UMLS; 2) Logical approach-We leverage subsumption relations in HPO to infer partial mappings to SNOMED CT; 3) Comparison-We analyze the specific contribution of each approach and evaluate the quality of the partial mappings through manual review.
resultsThere are 7358 HPO concepts with no complete mapping to SNOMED CT. We identified partial mappings lexically for 33% of them and logically for 82%. We identified partial mappings both lexically and logically for 27%. The clinical relevance of the partial mappings (for a cohort selection use case) is 49% for lexical mappings and 67% for logical mappings.
conclusionsThrough complete and partial mappings, 92% of the 10,454 HPO concepts can be mapped to SNOMED CT (30% complete and 62% partial). Equivalence mappings between HPO and SNOMED CT allow for interoperability between data described using these two systems. However, due to differences in focus and granularity, equivalence is only possible for 30% of HPO classes. In the remaining cases, partial mappings provide a next-best approach for traversing between the two systems. Both lexical and logical mapping techniques produce mappings that cannot be generated by the other technique, suggesting that the two techniques are complementary to each other. Finally, this work demonstrates interesting properties (both lexical and logical) of HPO and SNOMED CT and illustrates some limitations of mapping through UMLS.
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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.