ArticleCEUR workshop proceedings2014
Towards a foundational representation of potential drug-drug interaction knowledge.
Article in CEUR workshop proceedings, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Information needs for making clinical recommendations about potential drug-drug interactions: a synthesis of literature review and interviews.BMC medical informatics and decision making · 2017Pooled it
- An application-based ontological knowledge base of medications to support health literacy and adherence for the consumer population: an aging population use case.Journal of biomedical semantics · 2026Article
- A drug prescription recommendation system based on novel DIAKID ontology and extensive semantic rules.Health information science and systems · 2024Article
- Enriching the FIDEO ontology with food-drug interactions from online knowledge sources.Journal of biomedical semantics · 2024Article
- The use of foundational ontologies in biomedical research.Journal of biomedical semantics · 2023Review
- Testing the face validity and inter-rater agreement of a simple approach to drug-drug interaction evidence assessment.Journal of biomedical informatics · 2020Article
- Automatically classifying the evidence type of drug-drug interaction research papers as a step toward computer supported evidence curation.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020Article
- A Minimal Information Model for Potential Drug-Drug Interactions.Frontiers in pharmacology · 2020Article
- Detection of drug-drug interactions through data mining studies using clinical sources, scientific literature and social media.Briefings in bioinformatics · 2018Review
- Extending the DIDEO ontology to include entities from the natural product drug interaction domain of discourse.Journal of biomedical semantics · 2018Article
- Therapeutic indications and other use-case-driven updates in the drug ontology: anti-malarials, anti-hypertensives, opioid analgesics, and a large term request.Journal of biomedical semantics · 2017Article
- Formalizing Evidence Type Definitions for Drug-Drug Interaction Studies to Improve Evidence Base Curation.Studies in health technology and informatics · 2017Article
- Adding evidence type representation to DIDEO.CEUR workshop proceedings · 2016Article
- An accurate and precise representation of drug ingredients.Journal of biomedical semantics · 2016Article
- Toward a complete dataset of drug-drug interaction information from publicly available sources.Journal of biomedical informatics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Inadequate representation of evidence and knowledge about potential drug-drug interactions is a major factor underlying disagreements among sources of drug information that are used by clinicians. In this paper we describe the initial steps toward developing a foundational domain representation that allows tracing the evidence underlying potential drug-drug interaction knowledge. The new representation includes biological and biomedical entities represented in existing ontologies and terminologies to foster integration of data from relevant fields such as physiology, anatomy, and laboratory sciences.
Indexed as
Identifiers
33139970PMC7603806What 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.