Mapping clinical phenotype data elements to standardized metadata repositories and controlled terminologies: the eMERGE Network experience. - Wikidata - wikimedia - TriplyDB

Mapping clinical phenotype data elements to standardized metadata repositories and controlled terminologies: the eMERGE Network experience.

Mapping clinical phenotype data elements to standardized metadata repositories and controlled terminologies: the eMERGE Network experience.

http://www.wikidata.org/entity/Q33906590

about

Common data elements for spinal cord injury clinical research: a National Institute for Neurological Disorders and Stroke project Clinical research informatics: a conceptual perspective Standardizing clinical laboratory data for secondary use Identifying disease mutations in genomic medicine settings: current challenges and how to accelerate progress Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources An integrated, ontology-driven approach to constructing observational databases for research Multilingual Medical Data Models in ODM Format: A Novel Form-based Approach to Semantic Interoperability between Routine Healthcare and Clinical Research Leveraging EHR data for outcomes and comparative effectiveness research in oncology Ten Simple Rules to Enable Multi-site Collaborations through Data Sharing Ontology-based data integration between clinical and research systems Some experiences and opportunities for big data in translational research.Future translational applications from the contemporary genomics era: a scientific statement from the American Heart Association Development of a multi-institutional cohort to facilitate cardiovascular disease biomarker validation using existing biorepository samples linked to electronic health records.The Analytic Information Warehouse (AIW): a platform for analytics using electronic health record data."Big data" and the electronic health record.Clinical research informatics and electronic health record data Clinical Data Element Ontology for Unified Indexing and Retrieval of Data Elements across Multiple Metadata Registries.Examining Researcher Needs and Barriers for using Electronic Health Data for Translational Research.The GAAIN Entity Mapper: An Active-Learning System for Medical Data Mapping.ODMedit: uniform semantic annotation for data integration in medicine based on a public metadata repository.Improving risk prediction for depression via Elastic Net regression - Results from Korea National Health Insurance Services Data Discriminative and Distinct Phenotyping by Constrained Tensor Factorization.Phenome-wide association studies demonstrating pleiotropy of genetic variants within FTO with and without adjustment for body mass index Abstractions for Genomics Evaluation of matched control algorithms in EHR-based phenotyping studies: a case study of inflammatory bowel disease comorbidities Automated UMLS-based comparison of medical forms.Feasibility of using Clinical Element Models (CEM) to standardize phenotype variables in the database of genotypes and phenotypes (dbGaP).Solving the interoperability challenge of a distributed complex patient guidance system: a data integrator based on HL7's Virtual Medical Record standard.Cross border semantic interoperability for clinical research: the EHR4CR semantic resources and services Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network A unified structural/terminological interoperability framework based on LexEVS: application to TRANSFoRm.Automated Detection of Systematic Off-label Drug Use in Free Text of Electronic Medical Records Temporal abstraction-based clinical phenotyping with Eureka!PhenDisco: phenotype discovery system for the database of genotypes and phenotypes.A review of approaches to identifying patient phenotype cohorts using electronic health records.Integrating Bio-ontologies and Controlled Clinical Terminologies: From Base Pairs to Bedside Phenotypes.Building a Natural Language Processing Tool to Identify Patients With High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes.EHR-based phenotyping: Bulk learning and evaluation.Introducing the Big Knowledge to Use (BK2U) challenge.Surrogate-assisted feature extraction for high-throughput phenotyping.

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P2860

Mapping clinical phenotype data elements to standardized metadata repositories and controlled terminologies: the eMERGE Network experience.

http://www.wikidata.org/entity/Q33906590

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2011 nî lūn-bûn

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2011 թուականի Մայիսին հրատարակուած գիտական յօդուած

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2011年の論文

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Mapping clinical phenotype dat ...... the eMERGE Network experience.

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Mapping clinical phenotype dat ...... the eMERGE Network experience.

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Mapping clinical phenotype dat ...... the eMERGE Network experience.

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AMIAJNL-2010-000061

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Journal of the American Medical Informatics Association

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Mapping clinical phenotype dat ...... the eMERGE Network experience.

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Christopher G Chute

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Daniel R Masys

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Janey Wang

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Jyotishman Pathak

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Melissa Basford

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Rongling Li

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Sudha Kashyap

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P2860

Interface terminologies: facilitating direct entry of clinical data into electronic health record systems

The NCBI dbGaP database of genotypes and phenotypes

Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

The human phenome project

Why do it the hard way? The case for an expressive description logic for SNOMED

BioPortal: ontologies and integrated data resources at the click of a mouse

Mapping data elements to terminological resources for integrating biomedical data sources

Data standards in clinical research: gaps, overlaps, challenges and future directions

Comparing heterogeneous SNOMED CT coding of clinical research concepts by examining normalized expressions.

Creating mappings for ontologies in biomedicine: simple methods work.

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376-386

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scholarly article

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10.1136/AMIAJNL-2010-000061

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4

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18

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Jyotishman Pathak

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2011-05-19T00:00:00Z

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51150936

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21597104

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3128396

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