Preparing the Next Generation of Biostatisticians in the Era of Data and Translational Sciences
Preparing the Next Generation of Biostatisticians in the Era of Data and Translational Sciences
批准号:
10219349
负责人:
Sujit Kumar Ghosh
金额:
$24.98万
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:
2019-08-01 至 2024-07-31
关键词:
AddressAdoptionAreaAttentionAwardBioinformaticsBiomedical ResearchBiometryBiostatistical MethodsClinicalCollaborationsCommunitiesComplexComputational BiologyConceptionsDataData ScienceDevelopmentDisciplineElectronic Health RecordEnrollmentEnsureEnvironmentEvaluationEvidence Based MedicineExposure toFacultyFutureGenomicsGoalsHealth SciencesHealth systemImaging technologyInstitutionInternationalJointsKnowledgeLearningMedical ImagingMedical centerMethodologyMethodsModelingModernizationNamesNational Heart, Lung, and Blood InstituteNorth CarolinaObservational StudyParticipantPlayPoliciesPositioning AttributePrincipal InvestigatorProgram EffectivenessRequest for ApplicationsResearchResearch PersonnelResearch TrainingResourcesRoleSchoolsScienceScientistStatistical MethodsStrategic PlanningStructureStudentsTalentsTrainingTraining ProgramsTranslational ResearchTranslationsUnderrepresented PopulationsUnited States National Institutes of HealthUniversitiesanalytical methodbig biomedical datacareercareer developmentclinical trial analysiscohortcomputer sciencecomputerized toolsdata resourcedesigneducation researchexperiencefield tripgraduate studenthealth science researchinnovationinsightinstructorinterestinvestigator traininglaboratory experimentlectureslensmachine learning methodmultidisciplinarynext generationprogramspublic health researchrecruitresponseskillssoundstatistical and machine learningstatisticssummer institutesummer programsummer researchtoolundergraduate student
中文摘要
项目总结/摘要
在数据科学新兴计算工具的时代,生物统计学家需要发挥基础作用,
在健康科学研究中的作用。我们迫切需要鼓励美国公民和永久居民
进行生物统计学的研究生培训。临床试验的设计、实施和分析,
观察性研究;监管政策的制定;以及实验室实验的概念,
几十年来生物统计学家的基本贡献形成的。基因组学、医学、
成像技术和计算生物学;越来越强调精确性和循证医学
医学;以及电子健康记录的广泛采用;需要生物统计学家的技能
经过培训,能够在多学科环境中进行有效合作,
学习方法来应对这个数据丰富的健康科学革命时代带来的挑战
research.拟议的暑期课程,其中包括世界知名的临床科学家和
来自本地两所大学的生物统计学家,将为学生提供一个巨大的机会,学习
基本而现代的统计方法,对于从如此庞大而复杂的数据中发现新的见解至关重要。
生物医学数据,也说明了在分析时可能出现的混淆和偏见的潜在陷阱
生物医学数据。因此,拟议的培训方案的一个独特之处是,
不仅基本的统计方法,而且计算机科学和生物信息学的主题,这将是
在创建多学科团队以解决复杂的研究问题时,
需要多管齐下拟议的为期六周的培训计划将围绕
美国国立卫生研究院的翻译科学谱,并将介绍参与者在生物统计学的机会,通过
科学的透镜是由生物统计学家的贡献所推动的。经过最初几周的基础训练,
生物统计方法的培训,该计划将在数据黑客通村式的比赛中达到高潮,
参与者将利用在计划中获得的统计和科学知识,
创新、合理、科学相关和有效沟通的对策,
研究问题。拟议的研究教育计划将招收多达20名这样的参与者,
通过讲座、实地考察和分析来自真实的健康科学数据的机会,
鼓励他们继续深造。该计划将借鉴大量过去的合作,
两所本地世界知名大学的资源互补,为参加者提供无与伦比的
该领域的观点,包括获奖教师,国际知名的方法和临床
研究人员,以及一个有丰富机会展示生物统计学职业生涯的当地地区。将特别努力
从代表性不足的群体中招募参与者。完成后将跟踪参与者,
将记录统计学研究生院和从事生物统计职业的人数。
英文摘要
PROJECT SUMMARY/ABSTRACT
In the era of newly emerging computational tools for data science, biostatisticians need to play a fundamental
role in health sciences research. There is an urgent need to encourage US Citizens and Permanent Residents
to pursue graduate training in biostatistics. The design, conduct, and analysis of clinical trials and
observational studies; the setting of regulatory policy; and the conception of laboratory experiments have been
shaped by the fundamental contributions of biostatisticians for decades. Advances in genomics, medical
imaging technologies, and computational biology; the increasing emphasis on precision and evidence-based
medicine; and the widespread adoption of electronic health records; demand the skills of biostatisticians
trained to collaborate effectively in a multidisciplinary environment and to develop statistical and machine
learning methods to address the challenges presented by this data-rich revolutionary era of health sciences
research. The proposed summer program which includes world-renowned clinical scientists and
biostatisticians from two local universities, will provide an immense opportunity for student participants to learn
basic yet modern statistical methods that are critical to uncovering new insights from such big and complex
biomedical data and also illustrate the potential pitfalls of confounding and bias that may arise when analyzing
biomedical data. A unique feature of the proposed training program is thus to expose the participants to not
only basic statistical methods but also to the topics of computer science and bioinformatics which will be
invaluable in creating the multidisciplinary teams required to tackle the complex research questions that often
requires multipronged approaches. The proposed six-week training program will be structured around the
NIH's Translation Science Spectrum and will introduce participants to opportunities in biostatistics through the
lens of the science advanced by the contributions of biostatisticians. Following an initial set of weeks on basic
training of biostatistical methods, the program will culminate in a data hack-a-thon style competition in which
participants will employ the statistical and scientific knowledge gained during the program to produce the most
innovative, statistically-sound, scientifically-relevant and effectively-communicated response to a set of
research questions. The proposed research education program will enroll up to 20 such participants from
across the nation and, through lectures, field trips, and opportunities to analyze data from real health sciences,
inspire them to pursue graduate training. The program will draw upon considerable past collaborations and
complementary resources of two local world-renowned universities to provide participants with an unparalleled
view of the field, including award-winning instructors, internationally known methodological and clinical
researchers, and a local area rich in opportunities to showcase careers in biostatistics. Special efforts will be
made to enroll participants from underrepresented groups. Participants will be followed after completion, and
the numbers attending graduate school in statistics and pursuing biostatistics careers will be documented.
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Preparing the Next Generation of Biostatisticians in the Era of Data and Translational Sciences
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批准号:9888421
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项目类别:
-
资助金额:$24.98万
-
财政年份:2019
-
负责人:Sujit Kumar Ghosh
-
依托单位:
海外基金