Artificial Intelligence at NIH
The National Institutes of Health (NIH) makes a wealth of biomedical data available to research communities and aims to make these data findable, accessible, interoperable, and reusable—or FAIR. Additionally, NIH seeks to make these data usable with artificial intelligence and machine learning (AI/ML) applications. The ability to apply AI/ML techniques to biomedical research data has the potential to improve health and health care system operations, as well as increase the delivery of high-quality health care and positive patient health outcomes.
The National Institute of Biomedical Imaging and Bioengineering (NIBIB) defines AI and its components as:
Large datasets are central to the integration of AI in science and medicine, but many lack data on race, ethnicity, and social determinants of health, including considerations around minority health and health disparities in epidemiologic studies and prevention, diagnostic, and treatment interventions using AI.
AI applications could be particularly beneficial in places with limited access to health care, such as patients and populations in middle and low resource areas. Researchers are exploring clinical applications of AI; clinicians use AI to continuously learn and understand their patients; patients use AI to better understand themselves; society uses AI to complement and enhance human intelligence, rather than replace it; policymakers regulate AI to ensure its ethical and safe use.
- First mechanical calculating machine, French mathematician and inventor Blaise Pascal
- Image credit: Britannica.com
- First design for a programmable machine, Babbage and Lovelace
- Image credit: hackerearth.com
- Neural Networks established, McCulloch and Pitts
- Image credit: towardsdatascience.com
- Alan Turning introduces Turing Test for machine intelligence
- Image credit: Britannica.com
- "Artificial Intelligence" coined during Dartmouth Workshop
- By Source, Fair use, https://en.wikipedia.org/w/index.php?curid=14332488
- ELIZA natural language processing computer
- Image credit: analyticsindiamag.com
- Feigenbaum develops expert decision support system
- Image credit: https://en.wikipedia.org/wiki/Expert_system#/media/File:Symbolics3640_Mo...
- Deep Blue beats world chess champion Garry Kasparov
- Image credit: PRI.org
- iRobot launches Roomba
- Image credit: iRobot.com
- Google builds first urban self-driving car
- Image credit: wired.com
- IBM Watson wins Jeopardy!
- Image credit: cbsnews.com
- Personal Assistant, Siri
- Image credit: techcrunch.com
- AlphaGo beats professional Go player Lee Sedol
- Image credit: alphago
- Artificial Intelligence successfully diagnosed lung cancer in X-ray and CT scans
- Image credit: venturebeat.com
- GPT-3 — the biggest achievement of NLP
- Image credit: crowdbioticsblog.com
- Ingenuity is the first remote and AI-enabled object to fly on Mars
- Image credit: nasa.gov
- Due May 14: Administrative Supplements for Workforce Development at the Interface of Information Sciences, Artificial Intelligence and Machine Learning (AI/ML), and Biomedical Sciences (NOT-OD-21-079)
- Due May 26: Notice of Special Interest (NOSI): Administrative Supplements to Support Collaborations to Improve the AI/ML-Readiness of NIH-Supported Data (NOT-OD-21-094)
- Notice of Intent to Publish a Funding Opportunity Announcement for NIH Bridge2AI Integration, Dissemination, and Evaluation (BRIDGE) Center (U54) (NOT-RM-21-021)
- Notice of Intent to Publish a Research Opportunity Announcement for the Data Generation Projects of the NIH Bridge to Artificial Intelligence (Bridge2AI) Program (OT2) (NOT-RM-21-022)
Funded Research and Related Activities
Across NIH’s 27 institutes and centers, AI/ML technologies are being developed
- to detect and predict disease progression.
- for personalized therapies.
- for precision control (e.g., prosthetics).
- for automated monitoring of health.
- to identify risk and target intervention.
- for basic research (e.g., improving genome annotations with proteomic data).
- for use in healthcare.
Below are some specific examples:
National Human Genome Research Institute (NHGRI)
National Institute on Aging (NIA)
Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)
National Institute on Drug Abuse (NIDA)
National Institute of Mental Health (NIMH)
News, Events, and Publications
- April 7, 2021: NIH Strategically, and Ethically, Building a Bridge to AI (Bridge2AI) (National Library of Medicine)
- April 7, 2021: Using Artificial Intelligence To Uncover the Path to Health Restoration
- Oct 7, 2020: Machine learning detects early signs of osteoarthritis (NIA)
- Aug. 7, 2020: Release: NIH-funded project seeks to identify children at risk for MIS-C (NICHD)
- Feb. 14, 2020: Researchers use artificial intelligence to help predict heart attacks and strokes (National Heart, Lung, and Blood Institute)
- July 2019: Artificial intelligence needs high-quality data to deliver on promise (National Institute of Environmental Health Sciences)
- May 23, 2019: Spotlight: How artificial intelligence and other new technologies are advancing healthcare (NICHD)
- April 13-14, 2021: National Human Genome Research Institute's Genomic Data Science Working Group of the National Advisory Council for Human Genome Research host a virtual workshop titled “Machine Learning in Genomics: Tools, Resources, Clinical Applications and Ethics”
- Oct. 1, 2019: NIH AI Interest Group, Office of Intramural Research, and NIH AI Working Group for Autonomous Therapeutics hold a workshop titled “Artificial Intelligence Healthcare—From Prevention & Diagnostics to Treatments”
- July 12, 2019: National Center for Advancing Translational Sciences, National Cancer Institute, and NIBIB host workshop titled “Machine Intelligence in Healthcare: Perspectives on Trustworthiness, Explainability, Usability and Transparency”
- July 23, 2018: NIH Workshop: Harnessing Artificial Intelligence and Machine Learning to Advance Biomedical Research
- NIH Advisory Committee to the Director Working Group on AI: Presentation and Report (December 2019)
- Artificial Intelligence - Opportunities in Cancer Research
- Artificial Intelligence - NIBIB
This page last reviewed on May 1, 2021