Big Data Health Science Fellow Program in Infectious Disease Research

传染病研究大数据健康科学研究生计划

基本信息

批准号：
10311679
负责人：
Xiaoming Li
金额：
$ 35.1万
依托单位：
UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-08-04 至 2026-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10311679
关键词：
AIDS/HIV problem Academic Training Address Applications Grants Area Artificial Intelligence Big Data Big Data to Knowledge Biometry Businesses COVID-19 Cessation of life Clinical Clinical Medicine Communicable Diseases Communities Competence Data Data Science Data Scientist Data Sources Development Discipline Disease Disease Progression Education Projects Educational Curriculum Electronic Health Record Entrepreneurship Environment Face Faculty Fostering Funding Funding Agency Generations Genomics Goals HIV Health Health Care Research Health Policy Health Sciences Healthcare Individual Industry Infectious Diseases Research Information Technology Infrastructure Knowledge Machine Learning Manuscripts Measures Medicine Mentors Methodology Mission National Institute of Allergy and Infectious Disease Outcome Pharmacy facility Public Health Public Health Nursing Research Research Personnel Research Project Grants Research Proposals Schools Science Social Work South Carolina Strategic Planning Structure System Talents Technology Time Training Training Programs Underrepresented Populations United States National Institutes of Health Universities Virus Wages Workforce Development big-data science biomedical data science career cohort college community engagement comorbidity data acquisition data streams design digital experience financial incentive genomic data hands on research health data health science research health training high risk improved innovation interest medical schools mobile computing nanobiomaterial peer peer coaching prevent professor programs public health intervention public health relevance recruit skill acquisition skills social media synergism trend wearable device

项目摘要

Abstract The multiple, massive, and rich Big Data streams in healthcare (e.g., electronic health records, mobile technologies, wearable devices, genomic data) and the emergence of advanced information and computational technologies (e.g., machine learning and artificial intelligence) offer an invaluable opportunity for applying innovative Big Data science research in NIAID focus areas of infectious diseases such as HIV/AIDS and COVID-19. Big Data science has the potential to identify high-risk individuals and communities and prioritize them for early biomedical or public health interventions, predict long-term clinical outcomes and disease progression, and evaluate public health policy impact. Key to addressing these complexities is a critical mass of health researchers with adequate knowledge, competencies, and skills to unlock important answers from Big Data to better understand, treat, and ultimately prevent these diseases and related comorbidities. However, there is a nationwide shortage of talent with such knowledge, competencies, and skills, especially in traditional academic settings. While junior faculty, as part of the generations of digital learners, have the greatest potential to develop their Big Data health science research agenda, many face multiple structural barriers to conduct Big Data science research. Such barriers include a lack of protected time to initiate new interdisciplinary Big Data research, lack of opportunity to participate in funded Big Data research, and a lack of adequate mentoring. To address these gaps, we propose developing a “Big Data Heath Science Fellow” program for early career junior faculty (i.e., assistant professors) at health science schools (e.g., medicine, public health, nursing, pharmacy, social work) at the University of South Carolina (USC). Specifically, we plan to recruit 4 USC health science junior faculty per year and provide them with protected time (25%) to participate in the comprehensive training program, including: 1) courses for competency and skill development in Big Data research and professional development; 2) participation in hands-on research and grant proposal development; and 3) rich mentoring experience in Big Data research and professional development. The proposed training program will be implemented with the support of the existing infrastructure of the USC Big Data Health Science Center (BDHSC), one of USC’s Excellence Initiatives. BDHSC’s mission is to promote and support Big Data health science research at USC and across SC through capacity development, academic training, professional development, community engagement, and methodological advancement. BDHSC contains 5 content cores (electronic health records, geospatial, genomic, social media, and bio-nanomaterial data) and 2 supporting hubs (business/entrepreneurship and technology) with the involvement of 43 faculty from 10 USC college/schools. The proposed training will be an integral component of the BDHSC professional development mission. Upon the accomplishment of the proposed training, each trainee will be expected to: 1) obtain hands- on mentored research experience on an NIAID-funded project; 2) develop at least one Big Data-related manuscript on HIV or COVID-19; and 3) submit one grant application to NIAID or other appropriate funding source. The training program will foster a research environment to encourage individuals from diverse backgrounds, including those from underrepresented groups, to pursue further Big Data health science research in HIV, COVID-19, and other NIAID focus areas.

抽象的医疗保健领域的多个、海量且丰富的大数据流（例如电子健康记录、移动技术、可穿戴设备、基因组数据）以及先进信息和计算的出现技术（例如机器学习和人工智能）为应用提供了宝贵的机会 NIAID 的创新大数据科学研究重点关注艾滋病毒/艾滋病等传染病领域大数据科学有潜力识别高风险个人和社区并确定优先顺序。它们用于早期生物医学或公共卫生干预，预测长期临床结果和疾病解决这些复杂性的关键是临界质量拥有足够知识、能力和技能的健康研究人员，可以从大数据中解开重要答案数据可以更好地了解、治疗并最终预防这些疾病和相关合并症。全国范围内缺乏具有此类知识、能力和技能的人才，特别是在传统领域学术环境中，初级教师作为几代数字学习者的一部分，具有最大的潜力。为了制定大数据健康科学研究议程，许多人面临着开展大数据的多重结构性障碍这些障碍包括缺乏启动新的跨学科大数据的受保护时间。研究、缺乏参与受资助的大数据研究的机会以及缺乏足够的指导。为了解决这些差距，我们建议为早期职业青年开发“大数据健康科学研究员”计划健康科学学校（例如医学、公共卫生、护理、药学、具体来说，我们计划在南卡罗来纳大学 (USC) 招聘 4 名南加州大学健康科学专业的学生。每年为初级教师提供受保障的时间（25%）参加综合培训计划，包括：1）大数据研究和专业能力和技能发展课程开发；2) 参与实践研究和资助提案的制定；以及 3) 丰富的指导；拟议的培训计划将是大数据研究和专业发展的经验。在南加州大学大数据健康科学中心现有基础设施的支持下实施 (BDHSC) 是南加州大学卓越计划之一，BDHSC 的使命是促进和支持大数据健康。南加州大学和整个南加州大学通过能力发展、学术培训、专业 BDHSC 包含 5 个内容核心。（电子健康记录、地理空间、基因组、社交媒体和生物纳米材料数据）和 2 个支持中心（商业/创业和技术），有来自 10 USC 的 43 名教职人员参与学院/学校所提议的培训将是 BDHSC 专业发展的一个组成部分。完成拟议的培训后，每位学员将应： 1) 获得实际操作能力。拥有 NIAID 资助项目的指导研究经验； 2) 开发至少一项与大数据相关的项目；关于 HIV 或 COVID-19 的手稿；以及 3) 向 NIAID 或其他适当的资金提交一份资助申请该培训计划将营造一个鼓励来自不同来源的个人的研究环境。背景，包括来自代表性不足群体的背景，以进一步追求大数据健康科学 HIV、COVID-19 和其他 NIAID 重点领域的研究。