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Keep up with the latest news from the NCI Center for Biomedical Informatics and Information Technology (CBIIT) and the data science communities.

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Read NCI's Four Priority Areas for Artificial Intelligence

NCI Director Dr. Ned Sharpless and CBIIT Director Dr. Tony Kerlavage recently published an article, “The Potential of AI in Cancer Care and Research,” which takes stock of current advances in artificial intelligence and machine learning and outlines some of the areas NCI hopes to explore in greater depth in the future.

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National Library of Medicine Seeks Input on the Use of Common Data Elements in NIH-funded Research

NIH’s National Library of Medicine recently released a Request for Information (RFI) on the use of Common Data Elements (CDEs) in the context of research on COVID-19. These comments will be used to inform NIH’s continuing development of guidance on CDE use for COVID-related research. RFI responses are due by May 10, 2021.

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Smita Hastak Elected as HL7 Co-chair of Biomedical Research & Regulation Work Group

Ms. Smita Hastak, M.S., a senior analyst supporting NCI CBIIT, has been elected co-chair of Biomedical Research & Regulation at Health Level Seven International (HL7), an organization that provides standards for the exchange of health information and data.

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NIH Issues Notice Encouraging Adoption of U.S. Core Data for Interoperability Standard

NIH recently released a notice encouraging NIH-supported clinical programs and researchers to adopt and use U.S. Core Data for Interoperability (USCDI) standards. USCDI classifications will ensure clinical data adhere to a unified standard, allowing researchers to more easily compare different data sets and enabling more in-depth analysis to further scientific discovery.

Congratulations Metadata Automation DREAM Challenge Winners: C-Path Analytics, ENGRDynamics, and the CEDAR Team!

Metadata Automation DREAM Challenge Winners Announced

The Metadata Automation DREAM Challenge has closed! Learn more about the winners and how they plan to collaborate together to improve their algorithms and brainstorm future approaches to automating metadata annotation.

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