News

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

CAFCW23 brings together data and computational scientists, cancer biologists, and developers interested in accelerating the progress of computationally and data-driven cancer research and clinical applications.

NCI-funded researchers collaborated with scientists from Denmark to develop a deep learning tool for predicting risk for pancreatic cancer, an aggressive cancer that’s difficult to diagnose in the early stages of disease.

NCI’s Childhood Cancer Data Initiative has a new online Hub. If you’re a researcher, doctor, or citizen scientist, you now have quick-and-easy access to a rapidly growing inventory of data, tools, and resources on childhood cancer data.

Explore these two articles, both published by members of the NCI and Department of Energy Collaboration!

NCI-funded researchers used a machine learning approach to identify patients who were most likely to benefit, or have adverse effects, from cancer treatment late in life.

NCI-funded researchers collaborated with scientists from NCI’s Division of Cancer Epidemiology and Genetics and Division of Cancer Prevention on a study using a deep learning model to prioritize screening for lung cancer.

Discover how the algorithms produced in this challenge performed in detecting breast cancer.

Planning your itinerary for this year’s American Association for Cancer Research (AACR) Annual Meeting? Want to make sure you catch the NCI-affiliated data science activities? We’ve put together a helpful reference page for you!

NCI-funded researchers have developed a new artificial intelligence algorithm that’s helping identify the underlying biological causes of glioblastoma.

Using data from routine lung scans, NCI-supported researchers developed an AI-based tool to help predict how patients will respond to therapy.