Administration and Coordination Core (ACC)

行政和协调核心 (ACC)

• 批准号: 10386498
• 负责人: Bruce Y Lee
• 金额: $ 24.25万
• 依托单位: GRADUATE SCHOOL OF PUBLIC HEALTH AND HEALTH POLICY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-19 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10386498
• 关键词: Address; Affect; Area; Artificial Intelligence; Behavior; Communities; Complex; Computational Science; Computing Methodologies; Data; Data Collection; Data Science; Data Set; Development; Economics; Ensure; Environment; Ethics; Feedback; Goals; Grant; Health; Human Resources; Individual; Informatics; Information Systems; Intake; Laboratories; Lead; Modeling; Nutrient; Nutritional; Obesity; Organ; Outcome; Pathway interactions; Persons; Pilot Projects; Precision Health; Procedures; Process; Protocols documentation; Public Health; Publications; Research; Research Personnel; Rest; Running; Skin; System; Testing; Time; Vision; Work; absorption; base; complex data; computerized tools; computing resources; dietary; insight; nutrition; operation; precision nutrition; programs; social; tool; virtual; virtual human; virtual laboratory; working group

Abstract- Administration and Coordination Core (ACC) The vision of this proposed Artificial Intelligence, Modeling, and Informatics for Nutrition Guidance and Systems (AIMINGS) Center is to implement computational and data science approaches and tools to advance nutrition for precision health in a way that accounts for the complex systems involved. This involves a deep understanding of all of the factors and processes that affect different people's dietary behaviors and intake, absorption and processing of different nutrients, resulting in short- and long-term health outcomes, and the way each of these affect one another. Without assistance, it can be challenging to understand and address complex systems like nutrition and health. Cause-and-effect relationships cross different scales (e.g., cellular-level, organ-level, individual-level, social-and-environmental level), have various feedback loops, and evolve over time. Over the past two decades, computational power and data science have grown substantially. Used correctly, computational approaches can help fill in important gaps, lay out causal relationships, bring them together, and better characterize the system of nutrition; however, used incorrectly, such approaches can result in misleading insights that may incorporate biases and worsen existing disparities. Understanding and addressing complex systems requires both top-down and bottoms-up approaches. Using top-down approaches alone can lead to misconceptions and bias. In contrast, bottoms-up approaches work to rebuild the system by elucidating the mechanisms involved. The AIMINGS Center will aim to advance nutrition for precision health by building both top-down and bottoms-up approaches and tools to leverage existing data to its full potential. Such an approach could not only transform nutritional research and guidance but also do so with other areas of health. Many major health and public health problems are the result of broken systems and thus require more systems approaches to come up with more sustainable solutions. Aim 1 of the Administration and Coordination Core is to coordinate the Center operations to develop both top-down and bottoms-up computational approaches and tools to better understand and address the systems involved in precision nutrition in an ethical and unbiased manner. Aim 2 is to coordinate between the Center and across the Nutrition for Precision Health (NPH) consortium to develop shared approaches and procedures to advance the goals of the research program (e.g., developing protocols to work with data in an ethical and transparent manner, developing procedures and generating artificial intelligence-ready datasets). Aim 3 is to implement a Pilot Grant Program to expand the community of researchers and stakeholders who are working on computational approaches to understand complex data and systems in precision nutrition in an ethical manner. Aim 4 is to catalyze the broader development and use of computational methods and tools that help better understand and approach the systems that affect and are affected by nutrition in as ethical and unbiased manners as possible.

摘要-管理和协调核心(ACC) 这一提议的人工智能、建模和信息学的愿景是用于营养指导和 系统(目标)中心旨在实施计算和数据科学方法和工具，以 以一种考虑到所涉及的复杂系统的方式，促进精确健康的营养。这 包括对影响不同人饮食的所有因素和过程的深刻理解 行为和不同营养素的摄入、吸收和加工，从而产生短期和长期的健康 结果，以及这些结果相互影响的方式。在没有帮助的情况下，可能会面临挑战 了解并解决像营养和健康这样的复杂系统。因果关系交叉 不同的尺度(例如，细胞级别、器官级别、个人级别、社会和环境级别)具有不同的 反馈循环，并随着时间的推移而演变。在过去的二十年里，计算能力和数据科学 长势很大。正确地使用计算方法可以帮助填补重要的空白，展示因果关系 关系，将它们结合在一起，更好地描述营养系统；然而，如果使用不当， 这种方法可能导致误导性的见解，可能包含偏见，并加剧现有的差距。 理解和处理复杂系统需要自上而下和自下而上的方法。vbl.使用 单是自上而下的方法就会导致误解和偏见。相比之下，自下而上的方法可以 通过阐明所涉及的机制来重建系统。目标中心将致力于推进 通过构建自上而下和自下而上的方法和工具来实现精确健康的营养 充分利用现有数据的全部潜力。这样的方法不仅可以改变营养研究 和指导，但对其他卫生领域也是如此。许多主要的健康和公共卫生问题是 系统崩溃的结果，因此需要更多的系统方法来提出更可持续的方案 解决办法。管理和协调核心的目标1是协调中心的运营以发展 自上而下和自下而上的计算方法和工具，以更好地理解和解决 以道德和不偏不倚的方式参与精确营养的系统。目标2是协调 中心和跨精准健康营养(NPH)联盟开发共享方法和 推进研究计划目标的程序(例如，开发使用数据的协议 以合乎道德和透明的方式，制定程序和生成人工智能就绪的数据集)。 目标3是实施一项试点拨款计划，以扩大研究人员和利益相关者的社区 正在研究计算方法，以了解精确营养中的复杂数据和系统 合乎道德的态度。目标4是促进计算方法和工具的更广泛开发和使用 这有助于更好地理解和处理影响和受营养影响的系统，作为伦理和 尽可能不偏不倚的举止。