ArticleJournal of the American Medical Informatics Association : JAMIA2020
Time event ontology (TEO): to support semantic representation and reasoning of complex temporal relations of clinical events.
Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Clinical Decision Support and Natural Language Processing in Medicine: Systematic Literature Review.Journal of medical Internet research · 2024Pooled it
- Empowering clinical trial design with agentic intelligence and real-world data.Nature communications · 2026Article
- BSO-AD: An Ontology for Representing and Harmonizing Behavioral Social Knowledge in ADRD.medRxiv : the preprint server for health sciences · 2026Article
- Rendering knowledge graphs from aerospace dentistry processes for clinical decision support systems.Acta astronautica · 2026Article
- Development and evaluation of an ontology for non-invasive respiratory support in acute care.PloS one · 2026Article
- Temporal Ensemble Logic for Integrative Representation of the Entirety of Clinical Trials.LIPIcs : Leibniz international proceedings in informatics · 2025Article
- Comprehensive Ontology of Fibroproliferative Diseases: Protocol for a Semantic Technology Study.JMIR research protocols · 2023Article
- Computational Phenotyping of OMOP CDM Normalized EHR for Prenatal and Postpartum Episodes: An Informatics Framework and Clinical Implementation on All of Us.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- Ontologies and Knowledge Graphs in Oncology Research.Cancers · 2022Review
- Article
- Extracting postmarketing adverse events from safety reports in the vaccine adverse event reporting system (VAERS) using deep learning.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- ACE: the Advanced Cohort Engine for searching longitudinal patient records.Journal of the American Medical Informatics Association : JAMIA · 2021Article
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Authors and funding
14 authors.
Funding
Abstract
objectiveThe goal of this study is to develop a robust Time Event Ontology (TEO), which can formally represent and reason both structured and unstructured temporal information. MATERIALS AND
methodsUsing our previous Clinical Narrative Temporal Relation Ontology 1.0 and 2.0 as a starting point, we redesigned concept primitives (clinical events and temporal expressions) and enriched temporal relations. Specifically, 2 sets of temporal relations (Allen's interval algebra and a novel suite of basic time relations) were used to specify qualitative temporal order relations, and a Temporal Relation Statement was designed to formalize quantitative temporal relations. Moreover, a variety of data properties were defined to represent diversified temporal expressions in clinical narratives.
resultsTEO has a rich set of classes and properties (object, data, and annotation). When evaluated with real electronic health record data from the Mayo Clinic, it could faithfully represent more than 95% of the temporal expressions. Its reasoning ability was further demonstrated on a sample drug adverse event report annotated with respect to TEO. The results showed that our Java-based TEO reasoner could answer a set of frequently asked time-related queries, demonstrating that TEO has a strong capability of reasoning complex temporal relations.
conclusionTEO can support flexible temporal relation representation and reasoning. Our next step will be to apply TEO to the natural language processing field to facilitate automated temporal information annotation, extraction, and timeline reasoning to better support time-based clinical decision-making.
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