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

The letters "AI" appear in a box. Brightly colored lines feed into the box from all sides, showing how data flows into the box, where the information is then processed by AI.

New Regulations Aim to Make AI Models More Useful, Less Biased

Are you working on artificial intelligence (AI) solutions for cancer care? Check out these guidelines from the Office of the National Coordinator for Health Information, which should help make AI in clinical care more transparent.

Podcast Mic

NCI Podcast Comments on the Future of AI and Cancer Research

CBIIT Director Dr. Tony Kerlavage and NCI Chief Information Officer Mr. Jeff Shilling discuss the need for standardized data; the importance of addressing biases in artificial intelligence (AI) models; recruitment; and the necessity for continuous learning when it comes to AI.

Automatic segmentation of the liver from CT scan of patient TCGA-DD-A1EH

New Artificial Intelligence and Medical Imaging Annotations Added to the NCI Imaging Data Commons

Explore a new interactive dashboard that includes data sets of advanced machine-generated segmentation of tumor and organ contents.

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.

New Report Spotlights Research Gaps and Future Directions for Digital Twins

Interested in digital twin technology? Read this report for a “reality check” on what is currently known about the technology and what’s still missing.

icon representing the NIH Common Fund

Create Educational Courses and Encourage the Use of Common Fund Data Sets

This Notice of Funding Opportunity will allow you to create and run a short course to educate early career researchers on using data sets available in NIH’s Common Fund.

Illustration of a man’s upper torso, highlighting the lungs. In the background are dots and dashes to signify data. Concept is used to show the value of data in assessing lung disease.

Deep Learning Model Helps Predict Lung Cancer

A new deep learning model, called CXR-Lung-Risk, proved useful in identifying people at risk for dying from lung cancer or other lung disease, based on a single X-ray image.

close-up of computer chip

Opportunity for Data Scientists to Apply for AI Codeathon

If you’re a data scientist interested in artificial intelligence and machine learning codeathons, apply for this opportunity to build a solution for cancer!

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New NCI-Supported Platform for Open Data Challenges

Explore a resource that lets you search for data challenges that address areas of unmet medical need!

Data themed connectivity icons in background. Text reads, Request for Information

Deadline Extended: Tell Us if NCI Cancer Research Data Commons’ Data are Compatible with AI

NCI wants your input to help determine how compatible NCI’s Cancer Research Data Commons is with artificial intelligence applications. Explore this request for information to learn how to contribute!

Image shows a non-contrast low-dose chest CT scan. Three red dashed lines run across the chest scan and show the sections selected for body composition assessment.

Using AI to Assess Body Composition Could Help in Cancer Care

In a recent study, NCI-funded researchers applied an artificial intelligence model to lung screening computed tomography images to assess body composition. The team used two key indicators of health—skeletal muscle and fat (adipose) tissue—to predict death from lung cancer, cardiovascular disease, and other causes.

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