News

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

NCI wants your input on how to develop strong and useful benchmarks for artificial intelligence (AI) in cancer research. These benchmarks will help guide the development of AI tools that can improve how we prevent, detect, treat, and manage cancer.

Learn more about this NCI-funded tool that enables researchers like you to explore protein-centric, cancer omics data.

Want to use your data science skills to find better cancer treatments? See how these NCI-funded researchers working with artificial intelligence (AI) used information from a survival model to refine treatment for glioblastoma.

An NCI study reveals a connection between physical activity levels and cancer risk based upon data collected by researchers from wrist-worn sensors. Such devices are one of many examples of how big data science technologies can significantly drive the progress of cancer research.

Learn about this NCI-supported, comprehensive visual and interactive system for analyzing cell-to-cell interactions in 3D image data.

A new spatial transcriptomics tool, called Spotiphy, can help you visualize gene distribution patterns across entire tissue sections, giving you a more complete picture of the tumor and its microenvironment.

Having trouble discerning what makes a successful AI model? NCI is leading the way in developing concrete guidelines for building, evaluating, and reporting on AI-assisted prostate imaging models.

If you use or develop generative artificial intelligence (AI) in your cancer research, these important reminders about data security are for you!

See how a new AI-driven tool can help you measure micronuclei and similar structures to study their underlying biology, enabling you to more efficiently measure and characterize these tiny structures.

See how NCI-funded researchers built on previous studies to create a new model (called SMuRF) for head and neck cancer. Their model offers a new, more human-like, perspective to assessing head and neck cancer.