Big Data Health Science Scholar Program for Infectious Diseases

传染病大数据健康科学学者计划

• 批准号: 10655607
• 负责人: Neset Hikmet
• 金额: $ 13.83万
• 依托单位: UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-10 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10655607
• 关键词: Academic Training; Active Learning; Age; Area; Artificial Intelligence; Big Data; Biochemistry; Biomedical Engineering; Businesses; COVID-19; Caring; Cessation of life; Chemistry; Clinical Sciences; Communicable Diseases; Competence; Data; Databases; Development; Electronic Health Record; Entrepreneurship; Environment; Faculty; Fostering; Funding; Genomics; Goals; HIV; HIV/AIDS; Health; Health Sciences; Healthcare; Hour; Infectious Diseases Research; Information Technology; Infrastructure; Intelligence; Knowledge; Link; Machine Learning; Manuscripts; Mathematics; Measures; Mentors; Methodology; Mission; National Institute of Allergy and Infectious Disease; Outcome; Patients; Persons; Process; Public Health; Qualifying; Research; Risk; Scholars Program; Schools; Science; Scientist; South Carolina; Strategic Planning; Students; Talents; Technology; Training; Training Programs; Underrepresented Populations; United States; behavioral and social science; big-data science; college; community engagement; comorbidity; data streams; disease transmission; doctoral student; experience; faculty mentor; genomic data; hands on research; health data; health science research; improved; innovation; insight; interest; mobile computing; nanomaterials; next generation; pre-doctoral; programs; recruit; social media; statistics; summer research; training opportunity; wearable device

Abstract Today, a critical mass of previously collected linked health care data is now available for optimizing patient health outcomes. Information, insights, and intelligence existing in such health care data can be unlocked efficiently using Big Data Science (BDS).As people age and live longer, increased demand for care will be two-fold, one for those living with more comorbidities, and second the emergent risks from new infectious diseases like COVID-19.The recent NIAID strategic plan for COVID-19 highlights the urgent and important need for high-quality scientific research to improve knowledge around disease transmission, surveillance, and its impact on health outcomes, and to develop both biomedical and public health measures to mitigate illness and death. The existence of several massive, and information rich big data streams in healthcare (e.g., electronic health records [EHR], mobile technologies, wearable devices, genomic data, geospatial data etc.) and the advances in information and computational technologies (e.g., machine learning and artificial intelligence) now offer an excellent hands-on training opportunity for applying innovative Big Data science (BDS) research to infectious diseases such as HIV/AIDS and COVID-19. To cultivate a thriving and talented pipeline of next generation scientists, it is essential to engage current students early and provide new and innovative training opportunities to generate interest in the biomedical, social, and behavioral, and clinical sciences. Therefore, we propose offering a 10-week Short-Term Summer Research Training Program titled “Big Data Health Science Scholar Program for Infectious Diseases” targeted towards predoctoral students in physical and/or quantitative sciences (departments of biomedical engineering, integrated information technology, chemistry/biochemistry, mathematics, statistics etc.) from across South Carolina (SC) and the United States (US). Predoctoral students completing this training will engage in experiential learning through hands- on research in infectious disease areas like HIV/AIDS, and COVID-19, both relevant to the NIAID mission. Selected predoctoral students will be paired with Program Faculty mentors from a pool of distinguished participating faculty for one-on-one mentoring. Trainees will be chosen through a competitive process based on their proposed research plan and goals for the summer experience. Specifically, we plan to recruit 8 predoctoral students from physical and quantitative sciences across the US per year (a total of 40 over the entire funding period) to participate in the 10-week summer intensive training program with the following objectives: Objective 1: Create a summer big data science training pipeline for qualified predoctoral students by exposing them to relevant courses/training for competency development in the application of BDS to infectious disease research. Objective 2: Engage trainees in hands-on research using HIV and COVID-19 data. Objective 3: Provide trainees with rich research mentoring experience in BDS research and professional development for at least one year (summer included). The proposed training program will be implemented with support of the existing infrastructure of USC's Big Data Health Center (BDHSC). The BDHSC, one of the USC's Excellence initiatives, promotes and supports 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 (EHR, geospatial, genomic, social media, and bio-nanomaterial) and two supporting hubs (business/entrepreneurship and technology) with the involvement of 43 faculty from 10 USC college/schools. Upon the completion of the proposed training, each trainee is expected to: 1) complete 12 hours of academic training; 2) obtain hands-on BDS experience working on NIAID-funded research databases; and 3) develop at least one BDS manuscript on HIV or COVID-19 with their Program Faculty mentor. The training program will foster the research environment to encourage diverse applicants, 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 如今，之前收集的大量相关医疗保健数据现在可供使用 优化患者健康结果。 使用大数据科学 (BDS) 可以有效地解锁护理数据。随着人们的衰老和生活 更长的时间，对护理的需求将增加两倍，一是对于那些患有更多合并症的人， 其次是新的传染病（如 COVID-19）带来的新风险。最近的 NIAID COVID-19 战略计划强调了对高质量科学的迫切和重要需求 研究旨在提高有关疾病传播、监测及其影响的知识 健康成果，并制定生物医学和公共卫生措施来减轻疾病 和死亡中存在着多个海量且信息丰富的大数据流。 医疗保健（例如电子健康记录 [EHR]、移动技术、可穿戴设备、 基因组数据、地理空间数据等）以及信息和计算的进步 技术（例如机器学习和人工智能）现在提供了出色的实践机会 将创新大数据科学 (BDS) 研究应用于传染病的培训机会 培养下一代蓬勃发展的人才队伍。 一代科学家，有必要尽早让当前的学生参与进来并提供新的和 创新的培训机会，以激发人们对生物医学、社会和行为的兴趣， 因此，我们建议提供为期 10 周的短期夏季研究。 “传染病大数据健康科学学者计划”培训项目 针对物理和/或定量科学领域的博士前学生（系 生物医学工程、综合信息技术、化学/生物化学、 数学、统计学等）来自南卡罗来纳州 (SC) 和美国 (US)。 完成本次培训的博士前学生将通过实践进行体验式学习 HIV/AIDS 和 COVID-19 等传染病领域的研究，两者都与 选定的博士前学生将与来自 NIAID 的项目教师导师配对。 将选择一批杰出的参与教师进行一对一的指导。 通过基于他们提出的夏季研究计划和目标的竞争过程 具体来说，我们计划招收物理和定量博士前学生8名。 每年有 40 名美国各地的科学家（整个资助期内总共 40 名）参与 为期10周的夏季强化培训计划，其目标如下： 目标 1：为合格的博士前创建夏季大数据科学培训渠道 通过让学生接触相关课程/培训来培养他们的能力 北斗系统在传染病研究中的应用 目标 2：让学员利用 HIV 和 COVID-19 数据进行实践研究。 目标3：为学员提供丰富的北斗系统研究指导经验 专业发展至少一年（包括夏季）。 该计划将在南加州大学大数据健康现有基础设施的支持下实施 中心 (BDHSC)。 BDHSC 是南加州大学的卓越计划之一，负责促进和支持。 南加州大学和整个南加州大学通过能力发展进行大数据健康科学研究， 学术培训、专业发展、社区参与和方法论 BDHSC 包含 5 个内容核心（EHR、地理空间、基因组、社交媒体和）。 生物纳米材料）和两个支持中心（商业/创业和技术） 拟议项目完成后，来自 10 所南加州大学学院/学校的 43 名教师参与其中。 培训，每位学员应： 1) 完成 12 小时的学术培训； 2) 获得 在 NIAID 资助的研究数据库上工作的 BDS 实践经验；以及 3) 在 与他们的项目教师导师一起完成至少一篇关于 HIV 或 COVID-19 的 BDS 手稿。 计划将营造研究环境，鼓励多样化的申请者，包括那些 来自代表性不足的群体，以进一步开展艾滋病毒大数据健康科学研究， COVID-19 和其他 NIAID 重点领域。