NIH launches Bridge2AI program to expand the use of artificial intelligence in biomedical and behavioral research

Press release

Tuesday, September 13, 2022

The National Institutes of Health will invest $130 million over four years, pending funding availability, to accelerate the widespread use of artificial intelligence (AI) by the biomedical and behavioral research communities. The Bridge to Artificial Intelligence from the NIH Common Fund (Bridge2AI) is bringing together team members from diverse disciplines and backgrounds to generate richly detailed tools, resources, and data that respond to AI approaches. At the same time, the program will ensure that its tools and data do not perpetuate inequities or ethical issues that may occur during data collection and analysis. Through extensive cross-project collaboration, Bridge2AI researchers will create guidelines and standards for the development of ethically sourced, next-generation, AI-ready datasets that have the potential to help solve some of the most pressing challenges in technology. human health: how to discover how genetic, behavioral and environmental factors influence the physical condition of a person throughout his life.

“Generating high-quality, ethically sourced data sets is crucial to enabling next-generation AI technologies that transform the way we do research,” said Lawrence A. Tabak, DDS, Ph.D., Performing Duties from the Director of the NIH. . “Solutions to long-standing challenges in human health are at hand, and now is the time to connect researchers and AI technologies to address our toughest research questions and ultimately help to improve human health”.

AI is both a field of science and a set of technologies that allow computers to mimic how humans perceive, learn, reason, and act. Although AI is already used in biomedical research and healthcare, its widespread adoption has been limited in part due to the challenges of applying AI technologies to various types of data. This is because routinely collected biomedical and behavioral datasets are often understaffed, meaning they lack important contextual information about data type, collection conditions, or other parameters. Without this information, AI technologies cannot accurately analyze and interpret the data. AI technologies can also inadvertently incorporate bias or inequity, unless close attention is paid to the social and ethical contexts in which the data is collected. To harness the power of AI for biomedical discovery and accelerate its use, scientists first need well-described and ethically created datasets, standards, and best practices to generate biomedical and behavioral data that are ready for AI analytics.

As it builds tools and best practices to make data AI-ready, Bridge2AI will also produce a variety of diverse data types ready to be used by the research community for AI analytics. These types include voice and other data to help identify abnormal changes in the body. The researchers will also generate data that can be used to make new connections between complex genetic pathways and changes in cell form or function to better understand how they work together to influence health. In addition, AI-ready data will be prepared to help improve decision-making in critical care settings to speed recovery from acute illness and help uncover the complex biological processes underlying an individual’s recovery from illness.

The Bridge2AI program is committed to fostering formation of richly diverse research teams in perspectives, backgrounds, and academic and technical disciplines. Diversity is critical for the ethical generation of data sets and for training future AI technologies to reduce bias and improve efficacy for all populations, including those that are underrepresented in biomedical and behavioral research. Bridge2AI will develop ethical practices for data generation and use, addressing key issues such as privacy, data reliability and bias reduction.

NIH has issued four awards for data generation projects, and three awards create a Bridge Center for integration, dissemination and evaluation activities. The data generation projects will generate new ready-to-use biomedical and behavioral datasets to develop AI technologies, as well as create data standards and tools to ensure data is findable, accessible, interoperable and reusable, a principle known as FAIR. Additionally, data generation projects will develop training materials that promote a culture of diversity and the use of ethical practices throughout the data generation process. The Bridge Center will be responsible for integrating activities and knowledge into data generation projects and disseminating products, best practices, and training materials.

The Bridge2AI program is an NIH effort managed collaboratively by the NIH Common Fund, the National Center for Complementary and Integrative Health, the National Eye Institute, the National Human Genome Research Institute, the National Imaging Institute Biomedical and Bioengineering and the Library of Medicine. To learn more about the Bridge2AI program, visit Musings from the Mezzanine Blog from the National Library of Medicine, and look at this video about the Bridge2AI program.

About the NIH Common Fund: The NIH Common Fund fosters collaboration and supports a number of exceptionally high-impact trans-NIH programs. Common Fund programs are administered by the Office of Strategic Coordination in the Division for Program Coordination, Planning, and Strategic Initiatives within the Office of the Director of NIH in partnership with NIH Institutes, Centers, and Offices. More information is available on the Common Fund website: https://commonfund.nih.gov.

About the National Institutes of Health (NIH):NIH, the nation’s medical research agency, includes 27 institutes and centers and is a component of the U.S. Department of Health and Human Services. NIH is the lead federal agency that conducts and supports basic, clinical, and translational medical research , and is researching the causes, treatments, and cures for common and rare diseases. For more information about NIH and its programs, visit www.nih.gov.

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