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

基本信息

  • 批准号:
    10406058
  • 负责人:
  • 金额:
    $ 30.25万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 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

项目摘要

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是必不可少的,使翻译最近的科学数据, 覆盖来自两个常规信息源的观测的扩展频谱(例如,- 电子健康记录)和紧急方法(例如,基因组学、移动健康等)。事实上,生物医学信息学 和数据科学现在是临床护理以及科学知识进步的基础 与人类健康和疾病有关。这些方法使更多个性化的见解, 可以更好地指导医疗服务-精准健康的支柱。但是,仍然有一个有效的翻译- 必须克服的理论差距,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- 如何开发算法和工具,在广泛的多样性范围内实现公平的精准医疗 个人。 加州大学洛杉矶分校精准健康公平生物医学数据科学培训计划直接针对这一目标 姿势,培养一种新型的科学家在当代计算方法的交叉点训练, 生物医学信息学、公共卫生和精准医学。我们的学员将配备一个技术 深度,包括这些领域的能力,以及转化这些方法,以影响变革的能力。 医疗保健政策和实践,目标是为所有患者提供公平的药物。为此,T15带来了 汇集了来自我们机构和关键领域的领先科学家和临床医生,提供综合培训, 开放的,跨学科的方式,为学生提供在临床信息学,跨学科的主题的核心课程, 国家生物信息学、临床研究信息学和公共卫生信息学。它将为学员提供机会- 了解围绕精准健康的务实问题,并学习如何解决这些障碍 通过创新的研究和参与。教学课程和实践研究经验是 塑造,以加强技术和沟通技能,团队科学,并对社会的深刻赞赏, 技术问题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 随着时间的推移,T15将成为一个重要的增长领域,必须解决这个问题,以更好地为更大的人口提供服务。 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- 如果精准健康最终要代表每个人的话,这是一个根本的考虑。我们的学员将 灌输批判性的能力,是前瞻性思维,独立的科学家谁有效地促进跨, 培训,致力于通过改进计算方法来改善每个人的福祉。基础上 我们的教师在指导和建立开创性的科学方向方面的丰富经验,这 T15将建立新的科学领导者,他们将推动所需的变革,以实现精确的健康模式。

项目成果

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ALEX BUI其他文献

ALEX BUI的其他文献

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{{ truncateString('ALEX BUI', 18)}}的其他基金

Building BRIDGEs: Coordinating Standards, Diversity, and Ethics to Advance Biomedical AI
搭建桥梁:协调标准、多样性和道德以推进生物医学人工智能
  • 批准号:
    10801686
  • 财政年份:
    2023
  • 资助金额:
    $ 30.25万
  • 项目类别:
Building BRIDGEs: Coordinating Standards, Diversity, and Ethics to Advance Biomedical AI
搭建桥梁:协调标准、多样性和道德以推进生物医学人工智能
  • 批准号:
    10655487
  • 财政年份:
    2022
  • 资助金额:
    $ 30.25万
  • 项目类别:
Building BRIDGEs: Coordinating Standards, Diversity, and Ethics to Advance Biomedical AI
搭建桥梁:协调标准、多样性和道德以推进生物医学人工智能
  • 批准号:
    10473397
  • 财政年份:
    2022
  • 资助金额:
    $ 30.25万
  • 项目类别:
Predicting who will fracture: Exploration of machine learning in the observational Women's Health Initiative Study dataset.
预测谁会骨折:观察性妇女健康倡议研究数据集中机器学习的探索。
  • 批准号:
    10707881
  • 财政年份:
    2022
  • 资助金额:
    $ 30.25万
  • 项目类别:
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
  • 财政年份:
    2022
  • 资助金额:
    $ 30.25万
  • 项目类别:
Predicting who will fracture: Exploration of machine learning in the observational Women's Health Initiative Study dataset.
预测谁会骨折:观察性妇女健康倡议研究数据集中机器学习的探索。
  • 批准号:
    10370048
  • 财政年份:
    2022
  • 资助金额:
    $ 30.25万
  • 项目类别:
Network Core
网络核心
  • 批准号:
    10285908
  • 财政年份:
    2021
  • 资助金额:
    $ 30.25万
  • 项目类别:
Network Core
网络核心
  • 批准号:
    10657821
  • 财政年份:
    2021
  • 资助金额:
    $ 30.25万
  • 项目类别:
Prediction of Chronic Kidney Disease by Simulation Modeling to Improve the Health of Minority Populations
通过模拟模型预测慢性肾脏病以改善少数民族人群的健康
  • 批准号:
    10523518
  • 财政年份:
    2020
  • 资助金额:
    $ 30.25万
  • 项目类别:
Prediction of Chronic Kidney Disease by Simulation Modeling to Improve the Health of Minority Populations
通过模拟模型预测慢性肾脏病以改善少数民族人群的健康
  • 批准号:
    10087957
  • 财政年份:
    2020
  • 资助金额:
    $ 30.25万
  • 项目类别:

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