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; 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） 新颖的计算技术和统计技术对于能够翻译最近的科学疾病至关重要 来自两个常规信息源的观测范围的覆盖范围（例如Elec- Tronic健康记录）和新兴方法（例如基因组学，MHealth等）。确实，生物医学信息 数据科学现在是临床护理以及科学知识的发展的基础 与人类健康和疾病有关。这些方法正在增强更多单独限制的见解 可以更好地指导医疗保健交付 - 精确健康的支柱。尽管如此，仍然有效的翻译 由于当今的生物医学信息IAN和数据科学家需要更好地不足 立即开发算法和工具，以在广泛的多样性谱系中为公平的精确药物开发 个人。 加州大学洛杉矶分校的生物医学数据科学培训计划的精确健康公平计划直接针对此类 姿势，促进了在当代计算方法交集中培训的新型科学家， 生物医学信息，公共卫生和精密医学。我们的学员将配备技术 深度涵盖了这些领域，并能够翻译这种方法以影响转变 医疗保健政策和实践，目标是所有患者公平医学的目标。为此，这个T15带来了 来自我们机构和关键领域的主要科学家和临床医生共同提供培训 预科，跨学科的方式为学生提供临床信息的核心课程 理性的生物信息学，临床研究信息和公共卫生信息信息。它将负担得起的机会 - 看到围绕精度健康的务实问题并学习如何解决这些障碍的务实问题 通过创新的研究和参与。教学课程和动手研究经验是 旨在增强技术和沟通技巧，团队科学以及对社会的深刻欣赏 技术问题越来越多地与精度健康交织在一起。作为生物医学信息和数据科学 不断发展，该T15看到了一个重要的增长领域，必须解决，以更好地为人口众多。 我们的计划还通过我们的广泛包容性努力来进一步致力于多样性和公平 - 基本的考虑是否最终要代表所有人。我们的学员将是 灌输具有前瞻性的关键能力，独立科学家有效地有助于跨性别 编队，努力通过改进的计算方法来改善每个人的福祉。建立 我们教师在心态和建立开创性科学方向方面的丰富经验，这 T15将建立新的科学领导者，他们将推动需要改变以实现Precision Health范式。