Biomedical Data Science Training Program for Precision Health Equity

精准健康公平生物医学数据科学培训计划

• 批准号: 10615779
• 负责人: ALEX BUI
• 金额: $ 47.58万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10615779
• 关键词: Address; Affect; Algorithms; Area; Bioinformatics; Clinical Informatics; Clinical Research; Communication; Computing Methodologies; Data Science; Data Scientist; Disease; Educational Curriculum; Electronic Health Record; Equity; Faculty; Fostering; Genomics; Goals; Growth; Health; Health Policy; Human; Individual; Informatics; Institution; Knowledge; Learning; Medicine; Mentorship; Methods; Patients; Personal Satisfaction; Precision Health; Public Health; Public Health Informatics; Research; Science; Scientific Advances and Accomplishments; Scientist; Shapes; Source; Students; Techniques; Technology; Thinking; Training; Training Programs; Translating; Translations; biomedical data science; biomedical informatics; clinical care; diversity and equity; empowerment; experience; hands on research; health care delivery; health equity; improved; innovation; insight; mHealth; novel; precision medicine; programs; skills; tool

ABSTRACT (PROJECT DESCRIPTION) Novel computational and statistical techniques are essential for enabling the translation of recent scientific dis- coveries across the widening spectrum of observations from both conventional information sources (e.g., elec- tronic health records) and emergent methods (e.g., genomics, mHealth, etc.). Indeed, biomedical informatics and data science are now foundational to both clinical care as well as in the advancement of scientific knowledge related to human health and disease. These methods are empowering more individually-tailored insights that can better guide healthcare delivery – the mainstay of precision health. Still, there remains an effective transla- tional gap that must be overcome, as today’s biomedical informaticians and data scientists need to better under- stand how to develop algorithms and tools for equitable precision medicine across the wide diversity spectrum of individuals. The UCLA Biomedical Data Science Training Program for Precision Health Equity is aimed directly at this pur- pose, fostering a new type of scientist trained at the intersection of contemporary computational approaches, biomedical informatics, public health, and precision medicine. Our trainees will be equipped with a technical depth that embraces these areas alongside an ability to translate such approaches to affect the transform of healthcare policy and practice with a goal for equitable medicine for all patients. To that end, this T15 brings together leading scientists and clinicians from across our institution and key areas to provide training in a com- prehensive, interdisciplinary manner that offers students a core curriculum in topics in clinical informatics, trans- lational bioinformatics, clinical research informatics, and public health informatics. It will afford trainees opportu- nities to see the pragmatic issues surrounding precision health and to learn how to address these barriers through innovative research and engagement. Didactic coursework and hands-on research experiences are shaped to reinforce technical and communication skills, team science, and a deep appreciation for the socio- technological concerns increasingly intertwined with precision health. As biomedical informatics and data science evolves, this T15 sees to an important area of growth that must be tackled to better serve the larger populous. Our program also makes a further commitment to diversity and equity through our broad inclusion efforts – a fundamental consideration if precision health is to ultimately be representative of everyone. Our trainees will be instilled with the critical ability to be forward-thinking, independent scientists who effectively contribute to trans- formation, working to improve every individual’s well-being through improve computational methods. Building on our faculty’s extensive experience in mentorship and establishment of groundbreaking scientific directions, this T15 is set to establish new scientific leaders who will drive needed change to enable precision health paradigms.

摘要(项目描述) 新的计算和统计技术对于翻译最新的科学数据是必不可少的。 覆盖来自两个传统信息源(例如，电子- TRONIC健康记录)和应急方法(例如基因组学、移动健康等)。的确，生物医学信息学 数据科学现在既是临床护理的基础，也是科学知识进步的基础 关系到人类的健康和疾病。这些方法赋予了更多针对个人定制的洞察力 可以更好地引导医疗保健服务--精准健康的中流砥柱。尽管如此，仍然有一个有效的翻译- 必须克服的传统差距，因为今天的生物医学信息学家和数据科学家需要更好地了解- 了解如何在广泛的多样性范围内为公平的精确医学开发算法和工具 关于个人的。 加州大学洛杉矶分校生物医学数据科学精准健康公平培训计划就是针对这一问题- 姿势，培养出在当代计算方法的交叉点上培养出来的新型科学家， 生物医学信息学、公共卫生和精准医学。我们的实习生将配备技术人员 涵盖这些领域的深度，以及将这些方法转化为影响 医疗保健政策和实践，目标是为所有患者提供公平的医疗服务。为此，这款T15带来了 汇聚来自我们机构和关键领域的顶尖科学家和临床医生，提供COM- 全面、跨学科的方式，为学生提供临床信息学主题的核心课程，跨 国家生物信息学、临床研究信息学和公共卫生信息学。它将为实习生提供机会- 了解围绕精确健康的务实问题，并了解如何解决这些障碍 通过创新的研究和参与。授课课程和实践研究经验是 旨在加强技术和沟通技能、团队科学以及对社会的深刻理解- 技术方面的担忧越来越多地与精准健康交织在一起。作为生物医学信息学和数据科学 随着T15的发展，这是一个必须解决的重要增长领域，以更好地服务于更多的人口。 我们的计划还通过我们广泛的包容性努力进一步致力于多样性和公平-a 如果精确的健康最终要代表每个人，那么就需要基本的考虑。我们的实习生将是 被灌输了成为具有前瞻性思维的独立科学家的批判性能力，他们有效地促进了 编队，致力于通过改进计算方法来改善每个人的福祉。在基础上建设 我们的教员在指导和建立突破性的科学方向方面拥有丰富的经验，这 T15将建立新的科学领导者，他们将推动必要的变革，以实现精确的卫生范例。