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: 10406058
• 负责人: ALEX BUI
• 金额: $ 30.25万
• 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/10406058
• 关键词: Address; Affect; Algorithmic Software; Area; Bioinformatics; Clinical Informatics; Clinical Research; Communication; Computing Methodologies; Data Science; Data Scientist; Disease; Educational Curriculum; Electronic Health Record; Faculty; Fostering; Foundations; 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; Scientist; Source; Students; Techniques; Thinking; Training; Training Programs; Translating; Translations; biomedical data science; biomedical informatics; clinical care; diversity and equity; empowered; experience; hands on research; health care delivery; health equity; improved; innovation; insight; mHealth; novel; precision medicine; programs; skills

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） 新颖的计算和统计技术对于近期科学成果的转化至关重要。 覆盖了来自传统信息源（例如，电力）的不断扩大的观察范围 电子健康记录）和新兴方法（例如基因组学、移动健康等）。 数据科学现在是临床护理和科学知识进步的基础 这些方法正在提供更多针对个人的见解。 可以更好地指导医疗保健服务——精准健康的支柱，但仍然存在有效的翻译。 必须克服的差距，因为当今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 的个人。 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直接针对这一目标 提出，培养一种在当代计算方法的交叉点上接受训练的新型科学家， 我们的学员将配备生物医学信息学、公共卫生和精准医学的技术。 涵盖这些领域的深度以及将这些方法转化为影响变革的能力 医疗保健政策和实践的目标是为所有患者提供公平的医疗服务。为此，T15 提出了这一目标。 来自我们机构和关键领域的领先科学家和爱好者聚集在一起，在一个社区中提供培训 以全面、跨学科的方式为学生提供临床信息学、跨学科等主题的核心课程 理性生物信息学、临床研究信息学和公共卫生信息学将为学员提供机会。 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。 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 随着生物医学信息学和数据科学的发展，技术问题日益与精准健康交织在一起。 随着 T15 的发展，T15 看到了一个重要的增长领域，必须解决这个领域才能更好地服务于更多人口。 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性—— 精准健康最终要代表每个人，这是一个基本考虑因素。 灌输成为具有前瞻性思维的独立科学家的关键能力，为跨学科领域做出有效贡献 形成，致力于通过改进计算方法来改善每个人的福祉。 我们的教师在指导和建立突破性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，他们将推动所需的变革，以实现精准的健康范例。