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.

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 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.

Using data from routine lung scans, NCI-supported researchers developed an AI-based tool to help predict how patients will respond to therapy.

This newly released data set provides imaging in pediatric patients with newly diagnosed primitive neuroectodermal tumors throughout their treatment and until any potential relapse.

The latest update to the Childhood Cancer Data Catalog includes website improvements and the addition of the database of Genotypes and Phenotypes (dbGaP).

Learn how NCI CT (Computed Tomography) imaging data sets enable the use of artificial intelligence in planning treatment for non-small cell lung cancer.

An NCI training grant and resources such as the NCI Cancer Research Data Commons’ Genomic Data Commons, in part, made it possible for this study to use multimodal deep learning. This model allowed researchers to examine pathology whole slide images and molecular profile data from 14 cancer types to enable more accurate patient outcome predictions.

An artificial intelligence (AI)-driven, computer-aided diagnosis (CAD) software first developed by code writers’ physicians at NIH has received FDA clearance for the detection and diagnosis of prostate cancer. The tool, called ProstatID, combines AI with traditional MRI scanning.

TCIA has released three new data collections for cancer research. The new collections feature data from glioblastoma multi-parametric magnetic resonance imaging (mpMRI), a glioblastoma-based MRI Digital Reference Object (DRO), and data from colorectal digital biopsy slides.