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Studying pseudogout using naturallanguage processing and novelimaging approaches

Studying pseudogout using naturallanguage processing and novelimaging approaches
使用自然语言处理和新颖的成像方法研究假性痛风
批准号:
10359786
负责人:
Sara K. Tedeschi
金额:
$17.65万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-03-01 至 2024-02-29
关键词:
AcuteAffectAgeAgreementAlgorithmsAmericanArthritisAwardBioinformaticsBiological MarkersCalcium PyrophosphateCalcium pyrophosphate deposition diseaseCardiovascular DiseasesCase-Control StudiesChronicClinicClinicalClinical ResearchClinical SciencesClinical TrialsCodeCohort StudiesComplementComputerized Medical RecordConflict (Psychology)CrystallizationDataData AnalysesData SetDetectionDevelopmentDiagnosisDiureticsEnvironmentEquipmentEventFemaleFlareFoundationsFundingFutureGoalsGoldGoutGrantHealthcareHospitalsHypersensitivityImageImmunologyInflammatoryInflammatory ArthritisInfrastructureInstitutionInsurance Claim ReviewInterleukin-1 betaInterventionIschemic StrokeJointsKnowledgeLeadLinkLongitudinal StudiesMachine LearningManuscriptsMedicare claimMedicineMentored Patient-Oriented Research Career Development AwardMentorsMentorshipMethodsModalityMorbidity - disease rateMyocardial InfarctionNatural Language ProcessingOligonucleotidesOutcomeOutcome MeasureOutcomes ResearchPainPatientsPerformancePharmaceutical PreparationsPhysiciansPolyarthritidesPopulationPositioning AttributePredictive ValuePrevalencePrevention strategyProductivityProton Pump InhibitorsPseudogoutPublic Health SchoolsPublishingQuestionnairesResearchResearch PersonnelResourcesRheumatoid ArthritisRheumatologyRiskRisk FactorsRoentgen RaysSensitivity and SpecificitySerumSynovial FluidTechniquesTestingTimeTrainingUnited States National Institutes of HealthValidationVascular calcificationVascularizationVisitWagesWomanWorkX-Ray Computed Tomographyaccurate diagnosisbasebisphosphonatecalcium indicatorcardiovascular disorder riskcareercareer developmentcohortcrystallinityepidemiology studyexperiencegenetic linkage analysishigh riskhuman old age (65+)imaging modalityinstructorlongitudinal coursemedical schoolsmodifiable riskmortalitymortality riskmusculoskeletal imagingmusculoskeletal ultrasoundnovelpatient health informationpatient orientedpredictive modelingpreventprognosticprospectiveranpirnaserecruitresearch and developmentsexside effectstemstructured datatargeted treatmentultrasoundunnecessary treatment

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中文摘要
翻译
候选人:Tedeschi博士是哈佛医学院(HMS)的医学讲师和副教授
英文摘要
Candidate: Dr. Tedeschi is an Instructor in Medicine at Harvard Medical School (HMS) and Associate Physician in the Division of Rheumatology, Immunology and Allergy’s Section of Clinical Sciences (SCS) at Brigham and Women’s Hospital (BWH). She received an MPH from the Harvard T.H. Chan School of Public Health (HSPH). Her 10 first-author manuscripts, two BWH grants, and foundation award exemplify her productivity and commitment to research. She has assembled an experienced team of mentors and collaborators, led by Dr. Daniel Solomon (primary mentor) and Drs. Katherine Liao and Karen Costenbader (co-mentors), to guide her training in natural language processing and machine learning approaches for clinical research, analysis of linked electronic medical record (EMR) and Medicare claims data, and interpretation of advanced imaging modalities. Focused coursework at HSPH and HMS will complement the experience she gains through her proposed studies of pseudogout risk factors and long-term outcomes. Training in dual- energy CT and ultrasound interpretation for crystalline arthritis will be obtained via one-on-one sessions. Her long-term career goal is to become an independent patient-oriented investigator focused on pseudogout. Environment: Dr. Tedeschi has a commitment from her Division for >75% protected time for research and career development activities during the K23 award period. Support from the Division and her primary mentor’s research funds will supplement her salary and project-related expenses. The SCS, a collaborative clinical research group in the Division of Rheumatology, has extensive infrastructure including the VERITY Bioinformatics Core (NIH-P30-AR072577, PI: Solomon) that will provide resources and expertise for the proposed studies. In addition, the BWH Arthritis Center is one of the largest nationally, facilitating subject recruitment, and the BWH Division of Musculoskeletal Imaging has state-of-the-art equipment and expertise applying dual-energy CT in crystalline arthritis. Coursework at HSPH and HMS, adjacent to BWH, will provide training necessary for Dr. Tedeschi’s development into an independent investigator. Research: Dr. Tedeschi’s long-term objective is to prevent and reduce morbidity from pseudogout, an understudied, painful crystalline arthritis that affects 8-10 million Americans. She will use natural language processing and machine learning approaches to enhance an algorithm for identifying pseudogout in EMR data. She will study risk factors for and long-term outcomes in pseudogout, harnessing vast amounts of information contained in Partners HealthCare EMR data and Medicare claims data, and will gain experience working with linked datasets. Dr. Tedeschi will recruit subjects with pseudogout and other types of mono- and oligoarthritis to test and compare the performance of dual-energy CT scanning, musculoskeletal ultrasound, and x-ray for identifying pseudogout. Her proposed K23 projects will lead to manuscripts and data to be leveraged in an R01 application focused on pseudogout during the award period, leading to independence as a patient-oriented investigator.
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Studying pseudogout using naturallanguage processing and novelimaging approaches
  • 批准号:
    10578683
  • 项目类别:
  • 资助金额:
    $17.65万
  • 财政年份:
    2019
  • 负责人:
    Sara K. Tedeschi
  • 依托单位:
Studying pseudogout using natural language processing and novel imaging approaches
  • 批准号:
    10292824
  • 项目类别:
  • 资助金额:
    $5.4万
  • 财政年份:
    2019
  • 负责人:
    Sara K. Tedeschi
  • 依托单位:
海外基金