News

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

In the study, artificial intelligence (AI)-assisted contours outperformed manual contours, indicating the technology’s potential to enhance treatment strategies and improve outcomes for patients.

NCI-funded researchers used machine learning to characterize a cancer biomarker based on exosomes. Their biomarker worked well using non-invasive sources, such as blood and urine, allowing the researchers to catch cancer early, even in tumors of undetermined origins.

See how a new NCI-funded tool is helping scientists learn more about spatial gene expression, enabling them to use these data to better understand how cells relate—with their neighbors and within the tumor environment.

See how NCI researchers are using artificial intelligence to develop tools that may someday help oncologists make more informed decisions when caring for people with prostate cancer.

NCI-funded researchers are using machine learning to help identify an early-warning screening approach for colorectal cancer.

Want to identify existing gene mutations more accurately and discover new signatures more efficiently? There’s a new NCI-funded tool, the Mutational Signature Calculator, that can help improve your standard workflow.

Read the four-part series on NCI’s Cancer Research Data Commons’ history, resources, standards, and future initiatives. The articles are now available online in “Cancer Research,” one of the flagship journals of the American Association for Cancer Research (AACR).

Learn about the latest programs in NCI’s Childhood Cancer Data Initiative. A newly published summary offers an update on what’s underway and a forecast for future research.

Interested in digital twin technology? Read this report for a “reality check” on what is currently known about the technology and what’s still missing.

Learn how you can employ NCI’s semantic infrastructure to expand the use of CDISC standards for Real-World Data analysis and the generation of Real-World Evidence.