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

Hear the latest in digital twin development, technologies, and applications at Bio-IT World Conference and Expo.

NIH Institutes and Centers (including NCI) are interested in the validity, reliability, and utility of digital health tools and artificial intelligence/machine learning (AI/ML) technologies. You can apply for NCI funding to support the validation of these technologies for cancer research.

Are you planning to attend this year’s American Association for Cancer Research (AACR) Annual Meeting? Make sure to add these NCI-affiliated data science activities to your schedule!

Participate in the upcoming challenge to assess NCI Cancer Research Data Commons' compatibility with AI/ML technologies.

Do you conduct research on statistical and analytical methods, cancer survivorship, digital health, and/or data science tools and methods? Apply for an R01 grant from NCI’s Division of Cancer Control and Population Sciences by June 5 or October 5, 2024.

What if you could predict how a chemotherapy drug would work—in terms of sensitivity and side-effects—before you ever use it? NCI-funded researchers are using machine learning models to better understand a key mechanism underlying cancer, giving us new ways to predict responses to common chemotherapy drugs.

Are you working on artificial intelligence (AI) solutions for cancer care? Check out these guidelines from the Office of the National Coordinator for Health Information, which should help make AI in clinical care more transparent.

Explore a new interactive dashboard that includes data sets of advanced machine-generated segmentation of tumor and organ contents.

This Notice of Funding Opportunity will allow you to create and run a short course to educate early career researchers on using data sets available in NIH’s Common Fund.

NCI-funded researchers are using a machine learning approach to predict cancer outcomes based on epigenetic data, which take into account both environmental and genetic influences.