News

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

NCI-funded researchers combined long-term, patient-outcome data with pathology slides from people with colorectal cancer to develop a machine learning tool, called QuantCRC. Using QuantCRC, researchers could predict if a patient’s cancer would recur based on analysis of a single hematoxylin and eosin stained slide of the tumor.

See if any of the available grants highlighted in this Notice of Special Interest are a good fit for your data science work.

A new, NCI-funded, deep learning technology performed on par with radiologists in interpreting breast cancer images. This tool could help refine diagnosis to reduce the number of unnecessary biopsies.

NCI-DOE Collaboration researchers, using data from the Genomic Data Commons, have developed TULIP: a deep learning tool for classifying human RNA-seq-based tumor types.

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

Support the maintenance and enhancements of the Clinical Proteomic Tumor Analysis Consortium (CPTAC) Assay Portal, including the assay characterization data within it, through a new contract opportunity. Your proposal is due March 28, 2023.

Working with cancer data? NCI’s Office of Data Sharing invites you to give feedback on the processes you use to manage and share data.

NCI is seeking support for developing machine-generated segmentations of images in the radiology collections of the Imaging Data Commons (IDC). Submit your proposals by March 10, 2023.

NIH and NCI are participating in two funding opportunities to support the All of Us Research Program’s Researcher Workbench. These grants will help support analysis of the data for this program to advance research in cancer risk, early detection, prevention, diagnosis, treatment, cancer control, epidemiology, and health disparities.

You can use the funding to support data science training related to research on infectious- and immune-mediated disease, including cancer.