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.

Are you developing machine learning and looking for ways to make your model generalizable to a diverse population? A recent study describes an algorithm that centers on transforming your data rather than tweaking your model.

NIH is soliciting comments on a new draft of the Public Access Policy which will remove the 12-month embargo period for NIH-funded manuscripts and data.

Bring your ideas for reusing spatial omics and single-cell sequence data! Collaborate with researchers and coders on data interoperability, educational tools, and creative uses of the HTAN atlas data.

NCI’s Childhood Cancer Data Initiative seeks your feedback for the Pediatric Cancer Core Common Data Elements, a newly created resource which facilitates data integration and analysis.

Discover a new AI-driven tool that uses single-cell RNA data to help predict patient responses to cancer treatments.

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.

NCI has a new data science leader as of June 30, 2024! Meet Dr. Warren Kibbe. He’s bringing a wealth of experience to a brand new position at NCI—with the goal of advancing the use of data and data science in cancer research and care.

Learn about NCI’s LORIS, a new artificial intelligence-approach to help you predict how a patient will respond to immunotherapy.