National Infrastructure for Standardized and Portable EHR Phenotyping Algorithms
National Infrastructure for Standardized and Portable EHR Phenotyping Algorithms
批准号:
10021669
负责人:
YUAN LUO
金额:
$70.69万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2022-08-31
关键词:
AddressAdoptionAffectAlgorithmsArchitectureBenchmarkingBenign Prostatic HypertrophyClinicalClinical DataClinical ResearchClinical TrialsCodeCollaborationsCommunitiesComplexComputerized Medical RecordComputing MethodologiesConsensusConsumptionDataData ElementData ReportingDevelopmentEducational workshopElectronic Health RecordElectronic Medical Records and Genomics NetworkEngineeringEventExclusion CriteriaFast Healthcare Interoperability ResourcesFlowchartsGenomicsGoldGrantHealthHealth systemHealthcare SystemsHumanInformaticsInfrastructureIntuitionKnowledgeLogicMeasuresMedicalMethodsModelingNatural Language ProcessingNeeds AssessmentObservational StudyOutcomePatientsPerformancePhasePhenotypePrecision Medicine InitiativeProcessPublic HealthPublic Health InformaticsRare DiseasesResearchResearch PersonnelResolutionResourcesRisk FactorsRunningScientistServicesStandardizationStructureSystemTechniquesTextTimeTranslational ResearchUnited States National Institutes of HealthUniversity Hospitalsauthoritybasebiobankclinical phenotypecohortcomparative effectiveness studycomputable phenotypescostdata modelingdata warehousedatabase querydeep learningdesignendophenotypeexperienceinclusion criteriainformatics traininginformation modelknowledge basemeetingsphenotyping algorithmportabilityprecision medicinerepositorystructured datasyntaxtoolusability
中文摘要
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英文摘要
PROJECT SUMMARY
With the rapidly growing adoption of patient electronic health record systems (EHRs) due to Meaningful Use,
and linkage of EHRs to research biorepositories, evaluating the suitability of EHR data for clinical and
translational research is becoming ever more important, with ramifications for genomic and observational
research, clinical trials, and comparative effectiveness studies. A key component for identifying patient cohorts
in the EHR is to define inclusion and exclusion criteria that algorithmically select sets of patients based on
stored clinical data. This process is commonly referred to, as “EHR-driven phenotyping” is time-consuming
and tedious due to the lack of a widely accepted and standards-based formal information model for defining
phenotyping algorithms. To address this overall challenge, the proposed project will design, build and promote
an open-access community infrastructure for standards-based development and sharing of phenotyping
algorithms, as well as provide tools and resources for investigators, researchers and their informatics support
staff to implement and execute the algorithms on native EHR data.
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DOI:
10.1186/s12955-015-0285-6
发表时间:
2015-07-03
期刊:
Health and quality of life outcomes
影响因子:
3.6
作者:
[Ryu E, Takahashi PY, Olson JE, Hathcock MA, Novotny PJ, Pathak J, Bielinski SJ, Cerhan JR, Sloan JA]
通讯作者:
Sloan JA
DOI:
10.1038/gim.2013.121
发表时间:
2013-10
期刊:
Genetics in medicine : official journal of the American College of Medical Genetics
影响因子:
--
作者:
[]
通讯作者:
CQL4NLP: Development and Integration of FHIR NLP Extensions in Clinical Quality Language for EHR-driven Phenotyping.
CQL4NLP:在临床质量语言中开发和集成 FHIR NLP 扩展,以实现 EHR 驱动的表型分析。
DOI:
--
发表时间:
2021
期刊:
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
影响因子:
--
作者:
[Wen,Andrew, Rasmussen,LukeV, Stone,Daniel, Liu,Sijia, Kiefer,Rick, Adekkanattu,Prakash, Brandt,PascalS, Pacheco,JenniferA, Luo,Yuan, Wang,Fei, Pathak,Jyotishman, Liu,Hongfang, Jiang,Guoqian]
通讯作者:
Jiang,Guoqian
Integration of NLP2FHIR Representation with Deep Learning Models for EHR Phenotyping: A Pilot Study on Obesity Datasets.
NLP2FHIR 表示与 EHR 表型深度学习模型的集成:肥胖数据集的试点研究。
DOI:
--
发表时间:
2021
期刊:
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
影响因子:
--
作者:
[Liu,Sijia, Luo,Yuan, Stone,Daniel, Zong,Nansu, Wen,Andrew, Yu,Yue, Rasmussen,LukeV, Wang,Fei, Pathak,Jyotishman, Liu,Hongfang, Jiang,Guoqian]
通讯作者:
Jiang,Guoqian
DOI:
10.1016/j.jbi.2012.01.009
发表时间:
2012-08
期刊:
Journal of biomedical informatics
影响因子:
4.5
作者:
[Rea S, Pathak J, Savova G, Oniki TA, Westberg L, Beebe CE, Tao C, Parker CG, Haug PJ, Huff SM, Chute CG]
通讯作者:
Chute CG
共 31 条
Modeling the Incompleteness and Biases of Health Data
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批准号:10381541
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项目类别:
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资助金额:$31.13万
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财政年份:2020
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负责人:YUAN LUO
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依托单位:
Modeling the Incompleteness and Biases of Health Data
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批准号:10581658
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项目类别:
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资助金额:$30.75万
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财政年份:2020
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负责人:YUAN LUO
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In vivo Studies of Ginkgo biloba Neuroprotection
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批准号:7455616
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项目类别:
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资助金额:$4.5万
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财政年份:2004
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负责人:YUAN LUO
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依托单位:
In vivo Studies of Ginkgo biloba Neuroprotection
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批准号:7188740
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项目类别:
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资助金额:$19.48万
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财政年份:2004
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负责人:YUAN LUO
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依托单位:
In vivo Studies of Ginkgo biloba Neuroprotection
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批准号:7070002
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项目类别:
-
资助金额:$25.63万
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财政年份:2004
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负责人:YUAN LUO
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依托单位:
In vivo Studies of Ginkgo biloba Neuroprotection
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批准号:7283658
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项目类别:
-
资助金额:$25.63万
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财政年份:2004
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负责人:YUAN LUO
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依托单位:
In vivo Studies of Ginkgo biloba Neuroprotection
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批准号:6947778
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项目类别:
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资助金额:$3.9万
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财政年份:2004
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负责人:YUAN LUO
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依托单位:
In vivo Studies of Ginkgo biloba Neuroprotection
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批准号:7694239
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项目类别:
-
资助金额:$4.5万
-
财政年份:2004
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负责人:YUAN LUO
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依托单位:
In vivo Studies of Ginkgo biloba Neuroprotection
-
批准号:6827981
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项目类别:
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资助金额:$24.34万
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财政年份:2004
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负责人:YUAN LUO
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依托单位:
SIGNALING MECHANISMS IN DOPAMINE RECEPTOR SYNERGISM
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批准号:7235701
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项目类别:
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资助金额:$25.34万
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财政年份:2003
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负责人:YUAN LUO
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依托单位:
Mechanisms of Ginkgo biloba Neuropotection
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批准号:6534554
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项目类别:
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资助金额:$18.0万
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财政年份:2001
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负责人:YUAN LUO
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依托单位:
Mechanisms of Ginkgo biloba Neuropotection
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批准号:6860782
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项目类别:
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资助金额:$7.19万
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财政年份:2001
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负责人:YUAN LUO
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依托单位:
Mechanisms of Ginkgo biloba Neuropotection
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批准号:6435383
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项目类别:
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资助金额:$16.9万
-
财政年份:2001
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负责人:YUAN LUO
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依托单位:
FUNCTION OF G PROTEIN AND PCP2 IN CEREBELLUM DEVELOPMENT
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批准号:6084028
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项目类别:
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资助金额:$14.43万
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财政年份:2000
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负责人:YUAN LUO
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依托单位:
海外基金