ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2012
Using semantic web technologies for cohort identification from electronic health records for clinical research.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Predictors of new persistent opioid use after surgery in adults.Anesthesiology and perioperative science · 2025Article
- Assessing resolvability, parsability, and consistency of RDF resources: a use case in rare diseases.Journal of biomedical semantics · 2023Article
- Test collections for electronic health record-based clinical information retrieval.JAMIA open · 2019Article
- Integrating terminologies into standard SQL: a new approach for research on routine data.Journal of biomedical semantics · 2019Article
- Issues Associated With the Use of Semantic Web Technology in Knowledge Acquisition for Clinical Decision Support Systems: Systematic Review of the Literature.JMIR medical informatics · 2017Article
- SCALEUS: Semantic Web Services Integration for Biomedical Applications.Journal of medical systems · 2017Article
- Evaluation of Semantic Web Technologies for Storing Computable Definitions of Electronic Health Records Phenotyping Algorithms.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
- A novel framework for assessing metadata quality in epidemiological and public health research settings.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016Article
- Mining Electronic Health Records using Linked Data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2015Article
- Extension of GWAS results for lipid-related phenotypes to extreme obesity using electronic health record (EHR) data and the Metabochip.Frontiers in genetics · 2014Article
- Exploring the pharmacogenomics knowledge base (PharmGKB) for repositioning breast cancer drugs by leveraging Web ontology language (OWL) and cheminformatics approaches.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2014Article
- Using linked data for mining drug-drug interactions in electronic health records.Studies in health technology and informatics · 2013Article
- Applying semantic web technologies for phenome-wide scan using an electronic health record linked Biobank.Journal of biomedical semantics · 2012Article
- A review of approaches to identifying patient phenotype cohorts using electronic health records.Journal of the American Medical Informatics Association : JAMIAReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
The ability to conduct genome-wide association studies (GWAS) has enabled new exploration of how genetic variations contribute to health and disease etiology. One of the key requirements to perform GWAS is the identification of subject cohorts with accurate classification of disease phenotypes. In this work, we study how emerging Semantic Web technologies can be applied in conjunction with clinical data stored in electronic health records (EHRs) to accurately identify subjects with specific diseases for inclusion in cohort studies. In particular, we demonstrate the role of using Resource Description Framework (RDF) for representing EHR data and enabling federated querying and inferencing via standardized Web protocols for identifying subjects with Diabetes Mellitus. Our study highlights the potential of using Web-scale data federation approaches to execute complex queries.
Identifiers
22779040PMC3392057What 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.