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December 06, 2019 11:08 AM

VA dives into artificial intelligence R&D

Jessica Kim Cohen
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    AP

    The Department of Veterans Affairs has opened a new artificial intelligence institute to pursue research and inform national strategy.

    The National Artificial Intelligence Institute, a joint initiative of the VA's office of research and development and the VA secretary's center for strategic partnerships, will work with public and private partners to carry out AI research and development projects, including efforts to apply AI to identify veterans at high risk for suicide or to help reduce patient wait times.

    The institute will also collaborate with federal agencies on national AI strategy. That includes building upon the American AI Initiative, the national AI strategy President Donald Trump established through an executive order in February. The American AI Initiative's goal is to promote AI innovation in numerous sectors, including healthcare.

    The VA "has a unique opportunity to be a leader in artificial intelligence," VA Sec. Robert Wilkie said in a statement announcing the new institute.

    As a national health system, the VA has amassed a significant amount of data—possibly giving it a leg up, as lack of trustworthy and accessible data has, traditionally, been one of the major roadblocks to AI development. VA officials pointed to the Million Veteran Program, a genomic database that includes infromation from roughly 775,000 veterans, as an example.

    Gil Alterovitz, the VA's director of AI and a professor at Harvard Medical School, will lead the National Artificial Intelligence Institute.

    The VA's program is the latest example of federal health agencies pursuing work in AI.

    The CMS in March launched a $1.65 million contest to encourage development of understandable AI products for healthcare, with a focus on tools that can predict patient outcomes and adverse events. The FDA is in the midst of developing a strategy to regulate AI technologies, and in April solicited public comment on how it could use pre- and post-market evaluations to assess the safety of medical AI systems.

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