Building BRIDGEs: Coordinating Standards, Diversity, and Ethics to Advance Biomedical AI

搭建桥梁：协调标准、多样性和道德以推进生物医学人工智能

• 批准号: 10655487
• 负责人: ALEX BUI
• 金额: $ 247.75万
• 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 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10655487
• 关键词: Accountability; Advocate; Area; Artificial Intelligence; Behavioral; Behavioral Research; Benchmarking; Biomedical Research; Bridge to Artificial Intelligence; California; Caring; Collaborations; Communication; Communication Methods; Communities; Data; Data Analyses; Data Collection; Data Science; Data Set; Development; Discipline; Disparate; Disparity population; Education; Electronic Health Record; Elements; Ensure; Equilibrium; Equity; Ethics; Evaluation; FAIR principles; Feedback; Florida; Fostering; Future; Generations; Goals; Growth; Health; Healthcare; Heterogeneity; Image; Infrastructure; Institution; Leadership; Learning; Legal; Life; Life Cycle Stages; Measures; Methods; Michigan; Mission; Morphologic artifacts; Oregon; Outcome; Participant; Policies; Privacy; Process; Productivity; Publishing; Records; Reporting; Research; Science; Shapes; Source; Sum; Techniques; Technology; Touch sensation; Training; United States National Institutes of Health; Universities; Vision; Work; Workforce Development; biomedical informatics; cohesion; data tools; design; effectiveness evaluation; experience; forging; health care delivery; improved; innovation; insight; interest; mHealth; meetings; next generation; novel; programs; rapid technique; skill acquisition; skills; social; success; synergism; tool; tool development; trend; trustworthiness

OVERALL: ABSTRACT (PROJECT DESCRIPTION) Bridge2AI is a signature NIH initiative. It recognizes the challenges and opportunities in the growth of data sci- ence and data-driven methods for biomedical and behavioral research and healthcare delivery. We have reached a key moment: with the exponential growth of our ability to collect and analyze data, we must consider how we use this information to benefit everyone in an equitable way, providing a collective path forward. Data Generation Projects (DGPs) within Bridge2AI will tackle “grand challenges”: questions that will shape future scientific dis- covery and can ultimately impact the health and care of many. Marshalling these forces collectively requires experience and insight to create a collaborative, interdisciplinary endeavor that brings together disparate stake- holders to realize Bridge2AI’s mission: discovery, collaboration, and learning. Building from our collective experience in successfully guiding large NIH initiatives and (inter)national scientific consortia, our BRIDGE Coordination Center (CC) is designed to ensure a responsive set of Cores that will sup- port and enable the DGPs in their grand challenges. Representing multiple institutions (UCLA, Penn State Uni- versity, University of Florida, University of Michigan, University of Southern California, Oregon Health & Sciences University, Sage Bionetworks, EMBL-EBI), we propose multiple interacting Cores. These Cores have interdisci- plinary expertise across several key areas, including biomedical informatics/data science and AI (methods, ap- plications, evaluation), as well as across different domains and data types. Our Cores (Ethics, Standards, Tool Optimization, Skills & Workforce Development) are ready to interact to facilitate cross-cutting activities related to ethics and trustworthy artificial intelligence (ETAI); FAIR principles (findable, accessible, interoperable, reusable) across emergent datasets and domains; comparison and benchmarking of developed AI-ready datasets and tools. Across our CC we will create a basis for diverse trainees to not only appreciate the implications of AI in biomedical/behavioral research, but to meaningfully engage with them – embracing the heterogeneity of experi- ences, backgrounds, and objectives to maximize the richness and strength this diversity brings in our actions. We plan to work with a Teaming Core to enable activities that bring together disparate groups within Bridge2AI. Our efforts are organized by a skilled Administrative Core who will provide oversight and cohesion to this en- deavor, both across the Cores as well as with the DGPs and NIH. Our Cores are shaped to maximize the inte- gration and sharing of ideas across the DGPs and Bridge2AI as a whole through dynamic, contemporary com- munication methods; the refinement and dissemination of best practices between these groups and wider sci- entific community through multiple venues; and the evaluation of the effectiveness of the methods and overall Bridge2AI initiative. This CC will provide a unified framework for Bridge2AI to engage and education different stakeholders, and together blaze a collective trail forward for biomedical and behavioral AI – for everyone.

总体：摘要（项目描述） Bridge 2AI是NIH的一项标志性倡议。它认识到数据科学发展中的挑战和机遇， 为生物医学和行为研究以及医疗保健提供的证据和数据驱动的方法。我们已经达到 关键时刻：随着我们收集和分析数据的能力呈指数级增长，我们必须考虑如何 利用这一信息，以公平的方式造福于每个人，提供一条集体前进的道路。数据生成 Bridge 2AI中的项目（DGP）将解决“重大挑战”：将塑造未来科学发现的问题。 这可能会影响许多人的健康和护理。集结这些部队需要 经验和洞察力，创造一个协作，跨学科的奋进，汇集不同的利益， 持有人实现Bridge 2AI的使命：发现、协作和学习。 根据我们成功指导大型NIH倡议和（国际）国家科学研究的集体经验， 我们的BRIDGE协调中心（CC）旨在确保一组响应迅速的核心， 并使DGP能够应对其重大挑战。代表多个机构（加州大学洛杉矶分校，宾夕法尼亚州立大学， 大学，佛罗里达大学，密歇根大学，南加州大学，俄勒冈州健康与科学 大学，Sage Bionetworks，EMBL-EBI），我们提出了多个相互作用的核心。这些核心具有椎间盘间- 在几个关键领域的专业知识，包括生物医学信息学/数据科学和人工智能（方法，应用， 应用、评估），以及跨不同域和数据类型。我们的核心（道德、标准、工具 优化、技能和劳动力发展）随时准备互动，以促进与以下方面有关的跨领域活动： 伦理和可信人工智能（ETAI）;公平原则（可发现，可访问，可互操作，可重用） 跨新兴数据集和领域;比较和基准测试已开发的AI就绪数据集， 工具.在我们的CC中，我们将为不同的学员创造一个基础，不仅要欣赏人工智能的影响， 生物医学/行为研究，但要有意义地参与其中-拥抱经验的异质性， 我们的使命、背景和目标是最大限度地发挥这种多样性给我们的行动带来的丰富性和力量。 我们计划与Teaming Core合作，以实现将Bridge 2AI内不同团队聚集在一起的活动。 我们的努力是由一个熟练的行政核心谁将提供监督和凝聚力，这一en组织， Deavor，无论是在核心中还是在DGP和NIH中。我们的核心是为了最大限度地提高内部- 通过动态的、现代的通信，在整个DGP和Bridge 2AI之间进行交流和分享想法， 沟通方法;这些群体和更广泛的科学之间的最佳做法的完善和传播， 通过多个场地的有效性社区;和方法的有效性和整体的评价 Bridge 2AI倡议。该CC将为Bridge 2AI提供一个统一的框架， 利益相关者，并共同为生物医学和行为人工智能开辟一条集体道路-为每个人。