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

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
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-07-01 至 2026-04-30

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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.
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Building BRIDGEs: Coordinating Standards, Diversity, and Ethics to Advance Biomedical AI
Building BRIDGEs: Coordinating Standards, Diversity, and Ethics to Advance Biomedical AI
Predicting who will fracture: Exploration of machine learning in the observational Women's Health Initiative Study dataset.
Biomedical Data Science Training Program for Precision Health Equity
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