Curriculum in Biomedical Big Data: Skill Development and Hands-On Training

生物医学大数据课程：技能发展和实践培训

• 批准号: 9146562
• 负责人: MATTHEW H SAMORE
• 金额: $ 15.98万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-30 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9146562
• 关键词: Area; Big Data; Camping; Case Based Learning; Case Study; Categories; Clinical Sciences; Collaborations; Communication; Computerized Medical Record; Country; Data; Data Analyses; Data Reporting; Data Science; Data Set; Development; Discipline; Documentation; Educational Curriculum; Environment; Equilibrium; Evaluation; Faculty; Feedback; Foundations; Genomics; Goals; Health; Health Care Costs; Health Sciences; Healthcare; Healthcare Industry; Home environment; Imagery; Informatics; Interview; Knowledge; Language; Learning; Measures; Medicine; Methods; Molecular; Molecular Biology; Monitor; Participant; Process; Program Effectiveness; Recruitment Activity; Research; Research Personnel; Research Project Grants; Science; Scientist; Site; Skills Development; Sodium Chloride; Students; Surveys; Technology; Testing; Training; Training Programs; Universities; Utah; big biomedical data; biomedical informatics; case-based; clinical care; clinical decision-making; clinical investigation; data visualization; design; digital; educational atmosphere; evidence base; faculty mentor; flipped classroom; formative assessment; hands-on learning; improved; innovation; learning outcome; meetings; next generation; personalized medicine; population health; programs; research study; skill acquisition; skills; summer program

Project Summary Advances in genomics and biomedical generate huge amounts of data at the molecular level, while wide spread implementation of electronic medical records has dramatically increased digital documentation of healthcare information The objective of this proposal is to design, develop, and implement a cross-disciplinary, short-term training program in methods for utilizing Big Data in the health and biomedical science domain. Our curriculum will be organized as three two-week summer sessions: 1) “biomedical data science boot camp”; 2) “Targeted Learning with Case-Based Interdisciplinary Collaborative Learning,” and 3) "Integration, Exploration and Analysis of Heterogeneous Biomedical Data Sets for Prediction and Discovery”. Our program will include five knowledge categories: domain knowledge, computation, data representation, data visualization, and data analysis. These five areas will be integrated within an interactive learning environment that builds on principles of case-based learning and follows a flipped classroom paradigm. Program participants will be recruited from among trainees in biomedical informatics, molecular biology, population health sciences, and clinical investigation. Our curriculum will enable collaborating scientists to better comprehend the scientific language utilized in other disciplines. This will enhance communication and facilitate development of a synergistic environment which leads to improved overall quality of research studies. Upon completion of our short-term training, participants will be equipped to bootstrap their own big data research projects, participate in teams tackling big data problems in biomedicine, and pursue additional training in biomedical data sciences. The University of Utah is an ideal place for conducting this training with its superb collaborative academic environment. The University is home to the oldest academic biomedical informatics department in the country, Intermountain Healthcare is recognized as one of the world leaders in integrating informatics into clinical care, and the Salt Lake VA, is the center of VA's major informatics initiatives. Researchers from these three sites are being brought together to train the next generation of big data professionals equipped to propel data-driven analytics in medicine.

项目摘要 基因组学和生物医学的进步在分子水平上产生大量数据，而广泛 电子病历的传播实施已大大增加了数字文档 医疗保健信息本提案的目的是设计，开发和实施跨学科的， 在健康和生物医学科学领域中使用大数据的方法中的短期培训计划。我们的 课程将作为三个为期两周的夏季课程组织：1）“生物医学数据科学训练营”； 2） “针对基于案例的跨学科协作学习的有针对性的学习”，3）“集成，探索 以及对预测和发现的异质生物医学数据集的分析”。我们的计划包括 五个知识类别：领域知识，计算，数据表示，数据可视化和数据 分析。这五个领域将集成在互动学习环境中，以原则为基础 基于案例的学习，并遵循翻转的教室范式。计划参与者将从 在生物医学信息的学员中，分子生物学，人群健康科学和临床 调查。我们的课程将使科学家能够更好地理解科学语言 在其他学科中使用。这将增强沟通并促进协同的发展 环境会改善研究的整体质量。短期完成后 培训，参与者将配备自己的大数据研究项目，参与团队 解决生物医学中的大数据问题，并购买生物医学数据科学的其他培训。这 犹他大学是通过其出色的协作学术进行此培训的理想场所 环境。该大学是该国最古老的学术生物医学信息系的所在地， Intermountain Healthcare被认为是将信息纳入临床护理融入临床护理的世界领导人之一， 弗吉尼亚州盐湖（Salt Lake VA）是VA主要信息倡议的中心。这三个站点的研究人员是 聚集在一起培训配备数据驱动的下一代大数据专业人员 医学分析。