Mission

The NCI Center for Biomedical Informatics and Information Technology (CBIIT) provides for the appropriate use of data science, informatics, and IT, exemplifying a commitment to customer service, teamwork, pride, professionalism and resulting in optimal support of the NCI's mission to accelerate the prevention and treatment of cancer.

National Cancer Informatics Program

NCI established the National Cancer Informatics Program (NCIP) within CBIIT as the Institute's primary biomedical-informatics initiative. The NCIP will build on and extend investments that NCI has made during the past two decades to develop the informatics assets and computational approaches needed to support scientific discovery and clinical application in the postgenomics era.

CBIIT Speaker Series

On Wednesday, December 5, the CBIIT Speaker Series will feature a presentation on "A Systematic Approach to Building NLP Processes for Automated Extraction of Data from Clinical Reports" with Samir Courdy from Huntsman Cancer Institute and Dr. Joyce Niland from City of Hope.

The CBIIT Speaker Series is a bi-weekly knowledge-sharing forum featuring internal and external speakers discussing topics of interest to the biomedical informatics and cancer research communities. Visit the CBIIT Speaker Series page for more details. View previous presentations on the NCI CBIIT Speaker Series YouTube Playlist.

 

News

NCI Biomedical Informatics Blog

Check out the latest NCI Informatics blog post! The November 8 post, "Shape the Data Sharing Landscape: Make a Difference" is authored by Vivian Ota Wang, Ph.D., National Cancer Institute.

CBIIT leadership, staff, and guests from across NCI and the extramural community use this blog to discuss topics relevant to the future direction of NCIP and other NCI-supported research-and-development efforts centered on biomedical informatics and its role in furthering cancer research and care. Such topics include open-source and open-development initiatives, next-generation sequencing, the promulgation of standards to support interoperability, and challenges surrounding the study and analysis of large, complex data collections, most notably data management and integration.