News

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

Artists conceptualization of a digital twin. Shows the mirrored image of two heads. The only difference is one head is filled in with dots whereas the second head has spaces missing.

Cancer Patient Digital Twins—A Progress Report and Next Steps

Collaboration, cooperation, and the need for multimodal, multiscale data were central themes in a recent article on NCI’s efforts to develop a cancer research digital twin.

Stylized scan of torso with focus on liver and an orange colored cancer tumor

NCI Seeks Applications to Develop AI Models Using Secondary Data to Better Predict Abdominal Cancers

Learn more about a funding opportunity to develop AI-based models for predicting abdominal cancers. Applications may be accepted until May 8, 2023.

Silhouette image of of side portrait faces of five people that overlay each other. Three of the portriat faces are colored in light, medium and dark shades of red, one is in black and the last is shaded in torquise color.

NCI-Funded Partnership Uses AI to Improve Diversity in Cancer Clinical Trials

NCI-funded researchers recently began a partnership with AI experts from ConcertAI, LLC, to improve diversity in cancer clinical trials in the U.S. Gulf South region.

AI made out of abstract lines and dots

NIH’s Bridge2AI Program Launches to Increase AI in Biomedical and Behavioral Research

The NIH Common Fund’s Bridge to Artificial Intelligence program launched this month, aiming to bridge the gap between biomedical and behavioral research and artificial intelligence.

Artist conception of how NCI helps ideas to grow. The drawing shows a plant being watered and growing into a lightbulb, signifying how ideas take root and grow to fruition.

NCI Releases Contract Funding Opportunities for Digital Tools and Artificial Intelligence

NCI’s Small Business Innovation Research Development Center released four new contract funding topics. The topics aim to advance work in the fields of wearable technologies, digital tools, and artificial intelligence.

Blue torso and lungs with red-orange cancer spot. Text that says "AI"

Observational Study Shows Value in Using AI to Plan Radiotherapy for Lung Cancer

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

AI on blue data science background

NCI-Supported Study Uses Deep Learning for Cancer Prognosis

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.

The letters AI on a blue background with white interconnected dots.

AI-Driven Software Based Off NIH Algorithm Receives FDA Clearance in Detection and Diagnosis of Prostate Cancer

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.

#MICCAI2022 Breast Density FL Challenge. White text with a dark blue background, colorful flares coming from the bottom up.

Compete in the MICCAI 2022 Federated Learning Breast Density Challenge

Data scientists, informaticists, and medical physicists are invited to develop the best, most generalizable models, algorithms, and approaches for breast density estimation using image-based distributed or federated learning.

Cancer drug target visualized at the atomic level, the protein p97 is trapped in an inactive state by a new inhibitor (red) and the molecule cannot proceed into its normal reaction cycle. Image created using cryo-electron microscopy.

New NCI-DOE Collaboration Project, IMPROVE, Seeks Deep Learning Model Approaches

IMPROVE focuses on improving deep learning models to predict the efficacy of cancer treatments. The research community, including data scientists and informaticists, is asked to respond to an RFI for creating protocols to evaluate model performance by April 15, 2022, at 5:00 p.m. ET. Additionally, they are encouraged to respond to an RFP for improving model comparison by May 9, 2022.

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